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Minimum qualifications: Bachelor's degree in Computer Science, or equivalent practical experience. 5 years of customer-facing experience designing and deploying distributed data processing systems with one or more technologies. Experience with SQL data bases (e.g., PostgreSQL, MySQL, Oracle) and NoSQL data bases (e.g., Mongo, Cassandra.). Experience with different types of data modeling techniques and methodologies for traditional Online Analytical Processing or Online Transaction Processing (OLAP/OLTP) databases and modern data warehouses. Preferred qualifications: Certification in Cloud. 5 years of experience in managing technical client service. Experience reading software code in one or more languages such as Java, Python, NodeJS, Golang, JavaScript. Experience in devising migration approaches, and migrating on premise data processing systems to Cloud. Experience designing and deploying large-scale distributed data processing systems with one or more technologies: Oracle, SQL Server, MySQL, PostgreSQL, MongoDB, Cassandra, Redis, Hadoop, Spark, Flink, Kafka, Druid, Hive, HBase, Vertica, Netezza, Teradata, Tableau, or MicroStrategy. Knowledge of building and operationalizing data pipelines. About the jobThe Google Cloud Consulting Professional Services team guides customers through the moments that matter most in their cloud journey to help businesses thrive. We help customers transform and evolve their business through the use of Google’s global network, web-scale data centers, and software infrastructure. As part of an innovative team in this rapidly growing business, you will help shape the future of businesses of all sizes and use technology to connect with customers, employees, and partners. In this role, you will work with customers on critical projects to transform their business with data. You will provide consulting, solution design, and technical program management capabilities to customer engagements while directing customer executives and technical stakeholders on project related decisions. You will serve as a liaison between our customers and product teams to drive product excellence and adoption. In addition, you will also work with Google partners currently servicing accounts to manage programs, deliver consulting services, and provide technical guidance.Google Cloud accelerates every organization’s ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google’s cutting-edge technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.Responsibilities Work with customer technical leads, client executives, and partners to manage and deliver successful implementations of cloud solutions becoming a trusted advisor to decision makers throughout the engagement. Work with internal specialists, product and engineering teams to package best practices and lessons learned into thought leadership, methodologies, and published assets. Interact with business, partners, and customer technical stakeholders to manage project scope, priorities, deliverables, risks/issues, and timelines for successful client outcomes. Propose solution architectures and manage the deployment of cloud based databases, big data, and analytics solutions according to customer requirements and implement best practices. Travel up to 40% of the time for client engagements as needed. Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Google's EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form.

Minimum qualifications: Bachelor's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field. 10 years of experience using analytics to solve product or business problems, performing statistical analysis, and coding (e.g., Python, R, SQL) or 8 years of experience with a Master's degree. Preferred qualifications: Experience with developing at least one deep learning or conventional machine learning model for business impact. Experience debugging throughput, latency and response quality issues in AI products, from an analytical perspective. Experience managing large-scale data transformation pipelines for batch inference of ML models. About the jobHelp serve Google's worldwide user base of more than a billion people. Data Scientists provide quantitative support, market understanding and a strategic perspective to our partners throughout the organization. As a data-loving member of the team, you serve as an analytics expert for your partners, using numbers to help them make better decisions. You will weave stories with meaningful insight from data. You'll make critical recommendations for your fellow Googlers in Engineering and Product Management. You relish tallying up the numbers one minute and communicating your findings to a team leader the next. The Googler Technology and Engineering (GTE) team partners with teams across the company to apply Google’s best Data Science techniques to Google’s biggest enterprise opportunities. We partner with Research, Core Enterprise Machine Learning (ML) and ML Infrastructure teams to build solutions for our enterprise.The GTE Data Science team's mission is to:Transform Google Enterprise business operations, supply chain, IT support and internal tooling with AI and Advanced AnalyticsEnable operations and product teams to succeed in their advanced analytics projects through the use of differing engagement models, ranging from consulting to productionizing and deploying modelsBuild cross-functional services for use across Corporate EngineeringEducate product teams on advanced analytics and MLResponsibilities Define and report key performance indicators and launch impact as part of regular business reviews with the cross-functional and cross-organizational leadership team. Translate analysis results to business insights or product improvement opportunities.  Develop hypothesis to enhance performance of AI products on offline and online metrics through research on techniques around prompt engineering, RAG, supervised finetuning, in-context learning, dataset augmentation, tool-calling efficacy, planning capabilities and feedback loop with reinforcement learning. Design and develop ML strategies for data enrichment such as autoencoder based latent variables, complex heuristics etc. Evolve variance reduction and simulation strategies to increase reliability of experiments with small sample sizes. Unlock continually improving experimentation with algorithms like contextual bandits.  Convert business problems into unsupervised and supervised machine learning modeling problems, and build these model prototypes from scratch to justify business impact hypothesis. Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Google's EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form.

Logitech is the Sweet Spot for people who want their actions to have a positive global impact while having the flexibility to do it in their own way.The RoleLogitech is the Sweet Spot for people who want their actions to have a positive global impact while having the flexibility to do it in their own way.We are seeking a highly skilled Senior Data Scientist to join the Digital Growth Solutions organization. In this role, you will leverage your analytical skills, machine learning knowledge, and Gen AI-proficiency to uncover insights from commercial and customer service data.You will act as a technical bridge, supporting our Marketing Data Hub Product Owner and Segmentation Leads to drive data-informed decision-making across campaigns and digital experiences. This role blends immediate execution on our Customer Data Platform (CDP) with a strategic 12-18 month roadmap to build our internal Marketing Mix Modeling (MMM) capability.Your ContributionBe Yourself. Be Open. Stay Hungry and Humble. Collaborate. Challenge. Decide and just Do. These are the behaviors you’ll need for success at Logitech. In this role, you will:1. Advanced Analytics Machine LearningPredictive Modeling: Build, evaluate, and deploy predictive models using Python to solve real-world problems (e.g., churn prediction, LTV forecasting, and propensity scoring).Explainable AI: champion Explainable ML (e.g., SHAP values) to ensure non-technical stakeholders understand why a model is making specific recommendations.Generative AI: Integrate GenAI tools into data workflows to enhance productivity and generate insights from unstructured text (e.g., customer service logs).2. CDP Strategic CollaborationMarketing Data Hub: Support the Product Owner by designing analytic solutions that support specific business initiatives, ensuring our data strategy aligns with commercial goals.Segmentation Strategy: Partner with Segmentation Leads to perform targeted analysis, identifying meaningful customer patterns to refine our audience strategy.Actionable Insights: Translate complex findings into compelling stories via Tableau dashboards and visualizations that drive business action.3. Engineering Data FoundationsData Quality Pipelines: Evaluate data quality and propose cleaning strategies. Work with structured and unstructured data, designing efficient pipelines (using AWS Lambda, Athena) to ensure reliable data.Reproducibility: Develop reproducible data science workflows (not just ad-hoc scripts) in Jupyter Notebooks and productionize them via Snowflake.Marketing Mix Modeling (MMM): Over time, architect the end-to-end development of Logitech’s in-house MMM framework to measure ROI across online and offline channels.Key QualificationsFor this role, we need a blend of an Engineer’s discipline and a Statistician’s mind.Education Experience:Bachelor’s or Master’s degree in Computer Science, Statistics, Engineering, or a related field.8 years of experience in a Data Science role, specifically with a focus on marketing, customer analytics, or commercial data.Core Stack: Strong proficiency in Python (Pandas, NumPy, Scikit-learn) and SQL (Snowflake required).Cloud Architecture: Hands-on experience with AWS Cloud Services is a strong plus (SageMaker, S3, Athena, Lambda).Statistical Depth: Solid understanding of regression analysis, classification, time-series forecasting, and experimental design (A/B testing).Visualization: Experience with Tableau or similar BI tools for dashboarding.Business Acumen: Advanced proficiency in designing analytic solutions based on vague business requirements.Communication: Strong skills to present and engage with non-technical stakeholders (Marketing Directors, Finance partners).Autonomy: Ability to work independently in a fast-paced, matrixed environment.Curiosity: A Hungry and Humble attitude—willing to learn new stacks (like GenAI) and challenge the status quo.Across Logitech we empower collaboration and foster play. We help teams collaborate/learn from anywhere, without compromising on productivity or continuity so it should be no surprise that most of our jobs are open to work from home from most locations. Our hybrid work model allows some employees to work remotely while others work on-premises. Within this structure, you may have teams or departments split between working remotely and working in-house.Logitech is an amazing place to work because it is full of authentic people who are inclusive by nature as well as by design. Being a global company, we value our diversity and celebrate all our differences. Don’t meet every single requirement? Not a problem. If you feel you are the right candidate for the opportunity, we strongly recommend that you apply. We want to meet you!We offer comprehensive and competitive benefits packages and working environments that are designed to be flexible and help you to care for yourself and your loved ones, now and in the future. We believe that good health means more than getting medical care when you need it. Logitech supports a culture that encourages individuals to achieve good physical, financial, emotional, intellectual and social wellbeing so we all can create, achieve and enjoy more and support our families. We can’t wait to tell you more about them being that there are too many to list here and they vary based on location.All qualified applicants will receive consideration for employment without regard to race, sex, age, color, religion, sexual orientation, gender identity, national origin, protected veteran status, or on the basis of disability.If you require an accommodation to complete any part of the application process, are limited in the ability, are unable to access or use this online application process and need an alternative method for applying, you may contact us toll free at 1-510-713-4866 for assistance and we will get back to you as soon as possible.

Minimum qualifications: Bachelor's degree or equivalent practical experience. 6 years of experience in a management consulting, business strategy or corporate advisory role or program management. Preferred qualifications: MBA degree. Experience with data modeling and analysis to translate issues into insights. Experience in program management, including OKR development and the ability to move from granular detail to executive-level strategy. Knowledge of sales technologies, digital media products, and the market landscape for software or internet industries. Ability to lead operational initiatives in a changing environment. Excellent people management, and verbal and written communication skills, with the ability to influence executive-level audiences and cross-functional partners. About the jobAs a Strategy and Operations Lead within the Global Business and Operations (GBO) Tools team, you will lead critical priorities and projects. You will serve as a thought partner to business executives and key leaders, driving an understanding of global sales and support teams through technical enablement and automation. You will develop solutions for business problems. You will be at the forefront of transforming early-stage ideas into future-growth initiatives, helping to drive significant, multi-year business transformations currently underway within the Global Business Applied Artificial Intelligence (AI) (GBAI) ecosystem. You will collaborate with product management, engineering, and frontline sales and support teams to ensure the internal systems empower stakeholders and improve decision-making.Google Customer Solutions (GCS) sales teams are trusted advisors and competitive sellers who maintain a relentless focus on customer success by bringing the best Google has to offer to small- and medium-sized businesses (SMBs), which are the backbone of our communities. As a member of our team, you’ll have the opportunity to work with company owners and make a real difference in their businesses by helping them grow. Together, we help shape the future of innovation for customers, partners, and sellers...and we have fun doing it.Responsibilities Partner with cross-functional teams to define, structure, and drive end-to-end operational initiatives for GBO Tools. Enhance processes, drive change management, and improve business cadence through partnerships and effective project management. Enable critical decision-making by gathering cross-functional context, cross-pollinating learnings, and driving business analysis with effective communication. Lead key business cadences, including annual planning, objectives and key results (OKR) setting, and business reviews to align resources with organizational goals. Leverage internal and external data sources to create models, identify new opportunities, and deliver recommendations for business optimization. Build and support internal systems and dashboards that improve and streamline enablement flows for practitioners. Test leadership to align resources to business outcomes while managing global priorities and removing roadblocks to execution. Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Google's EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form.

Minimum qualifications: Bachelor's degree in Computer Science, a related technical field, or equivalent practical experience. 8 years of experience with technical management of software developers and system administrators/architects. Experience in building platforms that improve developer velocity, code quality and code health (e.g., compilers, automated releases, code design and testing, test automation frameworks). Experience with design and architecture of distributed systems, reliability fault tolerant systems, API design, and microservices architecture. Experience with software development in Python and C++. Experience with generative AI models. Preferred qualifications: Experience with enterprise-facing software, especially for providers in two-sided marketplaces. Experience with sign-up flows and other user-facing tools and flows. Experience with data modeling and serving APIs. Ability to work with course-correcting projects, challenging the status quo, and collaborating with cross-team, especially cross-timezone, to reach consensus quickly. Ability to presenting to and influencing executive technical leadership to drive complex decisions. About the jobGoogle's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. Our products need to handle information at massive scale, and extend well beyond web search. We're looking for engineers who bring fresh ideas from all areas, including information retrieval, distributed computing, large-scale system design, networking and data storage, security, artificial intelligence, natural language processing, UI design and mobile; the list goes on and is growing every day. As a software engineer, you will work on a specific project critical to Google’s needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. We need our engineers to be versatile, display leadership qualities and be enthusiastic to take on new problems across the full-stack as we continue to push technology forward.With your technical expertise you will manage project priorities, deadlines, and deliverables. You will design, develop, test, deploy, maintain, and enhance software solutions. YouTube OTT brings traditional movies, shows, and sports to YouTube. We package and promote this content through products like YouTube TV and primetime channels. Our businesses represent over 10 million subscribers and $XXB ARR worldwide.OTT Media is responsible for onboarding media companies, acquiring their premium TV content and metadata, modeling it, understanding and enriching it, packaging it, and ultimately publishing it to serving systems.We’re expanding our team in Bengaluru to bring 100x scale to content and media companies on YouTube. This team will build tools for media companies to manage and paygate their content on YouTube.At YouTube, we believe that everyone deserves to have a voice, and that the world is a better place when we listen, share, and build community through our stories. We work together to give everyone the power to share their story, explore what they love, and connect with one another in the process. Working at the intersection of cutting-edge technology and boundless creativity, we move at the speed of culture with a shared goal to show people the world. We explore new ideas, solve real problems, and have fun — and we do it all together.Responsibilities Take ownership of storage infrastructure, workflow, and pipelines for managing and publishing content to YouTube core. Build and manage tools in YouTube Studio for media companies to manage their content and grow their businesses on YouTube. Define, measure, and move metrics around data quality. Establish appropriate carrots and sticks to influence media companies to provide high quality videos and metadata on YouTube. Manage integration with 3P metadata providers. Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Google's EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form.

Minimum qualifications: Master's degree in a quantitative discipline such as Statistics, Engineering, Sciences, or equivalent practical experience. 4 years of experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis. Preferred qualifications: Experiences with experimental design and supervised/unsupervised machine learning approaches for both regression and classification tasks Experience of root cause analysis to ensure that problems are solved at both a tactical and strategic level. Experience delivering analysis, fully automated analytics pipelines or audience segmentation and propensity modeling. Understanding Bayesian approaches and modeling frameworks. Ability to generate practical solutions for marketing analytics problems and use results to drive business change in partnership with cross-functional stakeholders. About the jobGoogle's leadership team hand-picks thorny business challenges, and members of BizOps work in small teams to find solutions. As part of this team you fully immerse yourself in data collection, draw insight from analysis, and then zoom out to develop compelling, synthesized recommendations. Taking strategy one step further, you also persuasively communicate your recommendations to senior-level executives, roll-up your sleeves to help drive implementation and check back-in to see the impact of your recommendations. As a Data Scientist in the Marketing team, you will drive key measurement and analytics programs that deliver a scaled impact for Google Marketing across media campaigns. You will support the team by delivering pieces of project work including supporting the implementation of data science solutions, supporting the improvement of data pipelines, running geo-experiments or Marketing Mix Models (MMM) or helping your team develop evaluation metrics that provide insights to the business. You will own measurement and define milestones, provide direction for agencies/vendors, delegate, prioritize, plan, and direct a group of people to drive the project to completion.You will play a strategic and technical role in managing all things media, marketing, analytics, and partnering with internal teams to evaluate strategic initiatives. Using first-party and third-party data sources, you will create innovative solutions to demonstrate the effectiveness of Google’s media investment. At Google-scale, this implies working on our industry’s challenges. You will maintain global consistency, while keeping regional focus. You will be working with teams operating across regions and marketing entities.Responsibilities Use your knowledge of data analytics to develop solutions for marketing challenges, while also uncovering opportunities for measurement and optimization to push brand and performance marketing to the next level. Build measurement plans, tracking requirements, reporting, metrics and benchmarks for our largest campaigns to understand the incremental impact of our marketing dollars. (e.g. conversion lift tests, matched market analyses, and brand lift studies). Partner with internal teams in advanced analytics work including experimentation, measurement and modeling. Deliver customer-centric, data-driven approach, based on a people-based marketing strategy to build, segment, and test audiences for best business results. Develop evaluation frameworks for models, new metrics, and investigate anomalies. Frame and solve ambiguous problems by scoping technical priorities and innovating on statistical methods. Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Google's EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form.

Minimum qualifications: Bachelor's degree in Industrial engineering, Mechanical, or Electrical Engineering, a related technical field, or equivalent practical experience. 8 years of experience working as a Manufacturing Engineer in an industrial environment, within the Data Center space or Automotive production. Preferred qualifications: Certification in Six Sigma Black Belt, Lean Manufacturing. Experience with supplier technical evaluations, qualifications, and managing supplier relationships, with engineering and design software for modeling, analysis, and documentation. Experience with industry standards, including design guidelines for data center infrastructure. Understanding of Data Center cooling, with knowledge of electromechanical, networking, and mechanical assembly processes, tooling and equipment. Ability to lead complex manufacturing projects and mentor junior engineers, and to conduct data analysis to identify trends, root causes of defects, and measure manufacturing performance. Ability to travel up to 30%, and to identify and resolve manufacturing and quality issues. About the jobIn this role, your core mission is to bridge the gap between innovation and execution, ensuring the seamless flow of the product life-cycle from concept to delivery. You will drive product excellence through early engagement, utilizing comprehensive Design for Excellence (DFx) feasibility reviews and vendor capability assessments to eliminate red flag features and guarantee factory readiness.You will ensure operational precision by delivering accurate CapEx and tooling estimates, conducting should-cost analysis, and performing rigorous capacity validation via run-at-rate studies. You will be dedicated to building a resilient supply chain through proactive risk mitigation and test strategies. Furthermore, you will advocate operational excellence by optimizing material flow and driving continuous improvement through Lean manufacturing principles and Six Sigma methodologies to maximize efficiency and quality.Responsibilities Lead DFx reviews and generate Design for Manufacturing (DFM) reports during the concept readiness phase to identify and resolve red-flag features before design freeze. Validate production readiness through Run-at-Rate Validation reports and line balancing charts to align Takt time with cycle time. Execute vendor assessments and factory readiness gap analyses. Enforce process quality by reviewing process capability reports (Process Capability Index (Cpk) 1.33), control plans, and Measurement Systems Analysis reports during the pilot phase. Advocate risk management by leading PFMEAs with RPN reduction goals. Conduct Pareto and Eight Disciplines (8D) root cause analyses to resolve manufacturing issues. Optimize factory logistics via process flow diagrams and material plans to streamline production line supply. Validate test strategies and fixture designs, ensuring formal approval and sign-off. Oversee Engineering Change Order (ECO) implementations to re-validate fixtures as required. Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Google's EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form.

Minimum qualifications: Bachelor's degree or equivalent practical experience. 5 years of experience in data analysis, including identifying trends, generating summary statistics, and drawing insights from quantitative and qualitative data. 5 years of experience managing projects and defining project scope, goals, and deliverables. Preferred qualifications: 8 years of experience working on signal development, data analysis, cyber security or anti-abuse. Experience programming in one or more languages (e.g., Python, Golang). Experience working with complex engineering systems and processes. Experience with fraud/abuse investigations, fraud risk management, security and threat analysis in the context of internet, telephone, or communication-related products. Knowledge of SMS/MMS/RCS or SIM/phone number fraud and abuse. Excellent communication and presentation skills to deliver findings to cross-functional partners, and the ability to influence cross-functionally at various levels. About the jobTrust Safety team members are tasked with identifying and taking on the biggest problems that challenge the safety and integrity of our products. They use technical know-how, excellent problem-solving skills, user insights, and proactive communication to protect users and our partners from abuse across Google products like Search, Maps, Gmail, and Google Ads. On this team, youre a big-picture thinker and strategic team-player with a passion for doing what’s right. You work globally and cross-functionally with Google engineers and product managers to identify and fight abuse and fraud cases at Google speed - with urgency. And you take pride in knowing that every day you are working hard to promote trust in Google and ensuring the highest levels of user safety. The Trust and Safety (TS) team has the critical responsibility of protecting Googles users by ensuring online safety by fighting fraud and abuse across Google products.The Messaging Spam and Abuse team works on preventing abuse within the messaging ecosystem. We partner with product teams to identify potential abuse vectors ahead of new launches and establish, evaluate and maintain abuse protections.On this team, you're a big-picture thinker and strategic team-player with a passion for doing what's right. You understand the user's point of view and are passionate about using your technical, analytical, and strategic acumen to protect our users. You work globally and cross-functionally with Google Engineers and Product Managers to navigate challenging online safety situations and handle abuse and fraud at Google scale.At Google we work hard to earn our users’ trust every day. Trust Safety is Google’s team of abuse fighting and user trust experts working daily to make the internet a safer place. We partner with teams across Google to deliver bold solutions in abuse areas such as malware, spam and account hijacking. A team of Analysts, Policy Specialists, Engineers, and Program Managers, we work to reduce risk and fight abuse across all of Google’s products, protecting our users, advertisers, and publishers across the globe in over 40 languages.Responsibilities Analyze emerging trends, conduct complex data analyses and identify new signals to develop solutions for scaled enforcement. Develop a deep understanding of abuse in messaging, current cross-product workflows and available intelligence. Translate abuse protection requirements into data modeling initiatives and build prototypes. Collaborate with Engineering, Product Managers, Program Manager groups to develop requirements documents based on robust data analysis and granular product understanding. Perform active threat monitoring, identify gaps in abuse detection and constantly update abuse rules based on evolving patterns. Create real-time awareness of threats and educate clients to reduce the problem upstream. Lead projects to prevent Google's infrastructure from being abused to harm users or commit financial fraud resulting in losses to users and/or Google. Collaborate with the carrier ecosystem to block bad actors (e.g., corrective/preemptive measures, fraud investigations). Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Google's EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form.

Minimum qualifications: Master's degree in Statistics, Data Science, Mathematics, Physics, Economics, Operations Research, Engineering, or a related quantitative field, or equivalent practical experience. 8 years of work experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or 6 years of work experience with a PhD degree. Experience with statistical data analysis such as linear models, multivariate analysis, causal inference, or sampling methods. Experience with statistical software (e.g., SQL, R, Python, MATLAB, pandas) and database languages along with statistical analysis, modeling and inference. Preferred qualifications: PhD in a quantitative field. 10 years of experience with statistical data analysis such as linear models, multivariate analysis, stochastic models, and sampling methods. 5 years of leadership experience, including people management. Experience with Machine Learning (ML) on large datasets, with the ability to select the right statistical tools in a given data analysis problem. Understanding of potential outcomes framework and with causal inference methods such as split-testing, instrumental variables, difference-in-difference methods, fixed effects regression, panel data models, regression discontinuity, matching estimators, with knowledge of structural econometric methods. Ability to set and drive technical strategy. About the jobAs a Technical Lead on Google’s Advertising Measurement team, you will apply scientific aptitude, excellence, precision, accuracy, expertise, thoroughness and statistical expertise to navigate the complex challenges of a global, privacy-preserving advertising ecosystem. Google is a pioneer in sustaining an open internet through a mutually-reinforcing cycle of ad-planning, optimization, and measurement; in this strategic leadership role, you will be the recognized authority driving that cycle forward. You will develop, organize, and launch large-scale projects spanning engineering and analysis across Search, Display, YouTube, and beyond. By translating advanced science specifically causal inference and quantitative methodologies into deployed products, you will lead the charge in defining paradigm-shifting measurement standards for the future of digital advertising. Working cross-functionally with Engineers, Product Managers, and Sales, you will adjust global strategies based on your findings, ensuring advertising remains useful for users and results-driven for publishers. We are seeking quantitatively trained experts with a passion for business strategy and a deep appreciation for consumer behavior. In this role, you won’t just improve products; you will empower an exceptional team to shape the marketing-technology industry globally. If you thrive in fluid, science-driven environments and are ready to leverage data and technology to solve modern advertising’s greatest challenges, your leadership will be the catalyst for the next era of innovation.Responsibilities Apply causal inference and differential privacy methods to design experiments, assess attribution, and develop privacy-preserving marketing products. Execute end-to-end analyses including data gathering, EDA, and model development to deliver strategic insights to executives. Build iterative analysis pipelines and prototype data structures to provide scalable insights across Google’s complex data ecosystems. Collaborate with Product and Engineering team to define and answer quantitative questions regarding incrementality, user behavior, and bidding optimization. Provide technical guidance and prioritization for the team, conduct cost-benefit analyses to drive high-level business decisions and product strategy. Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Google's EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form.

Minimum qualifications: Bachelor's degree in Computer Science, Engineering, Mathematics, Operations Research, or a related quantitative field. 2 years of experience in developing and deploying Machine Learning models or AI-driven applications. Experience with agent-based modeling, predictive modeling, or deep learning architectures. Experience with prompt engineering. Preferred qualifications: Experience in Python and standard data science libraries (e.g., NumPy, pandas, scikit-learn, TensorFlow/PyTorch). Experience putting data science principles into practice, data quality assessment, statistical modeling, feature engineering, and data visualization. Experience with frameworks like LangChain or LlamaIndex, to build advanced, multi-step agents. Experience in using vector and graph databases to power Retrieval-Augmented Generation (RAG) in supply chain processes and systems. Experience working with cloud computing platforms (e.g., Cloud Computing Platform, Google Cloud Platform) and developing solutions that interact with large-scale data warehouses and databases (SQL, NoSQL). Familiarity with optimization techniques (linear programming, heuristic search) and simulation modeling. About the jobA problem isn’t truly solved until it’s solved for all. That’s why Googlers build products that help create opportunities for everyone, whether down the street or across the globe. As a Technical Program Manager at Google, you’ll use your technical expertise to lead complex, multi-disciplinary projects from start to finish. You’ll work with stakeholders to plan requirements, identify risks, manage project schedules, and communicate clearly with cross-functional partners across the company. You're equally comfortable explaining your team's analyses and recommendations to executives as you are discussing the technical tradeoffs in product development with engineers. Google Cloud accelerates every organization’s ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google’s cutting-edge technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.Responsibilities Design, build, and prototype AI agents focused on optimizing key supply chain functions for cloud compute infrastructure (e.g., forecasting, capacity planning, demand sensing, component procurement, logistics, and reverse logistics). Iterate on ideas, conducting rapid A/B testing and proof-of-concept experiments to validate the technical feasibility and business impact of agent-based solutions. Create comprehensive documentation, including technical specifications, model architecture, and model maintenance procedures to ensure a seamless and efficient transition of successful prototypes to production engineering teams. Run regression tests in production to validate model outcomes. Partner closely with Supply Chain Operations, Architects, Finance, and Engineering teams to define requirements, gather feedback, and ensure prototypes align with strategic business objectives and drive user adoption in production. Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Google's EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form.