Cake 找工作

建構與優化機器學習模型: 運用多維度運動數據（如賽事數據、球員表現），開發球員薪資計算、表現預測等核心模型，並持續進行優化。 支援產品與行銷決策: 深入分析用戶行為與市場趨勢，提供數據洞察，協助產品團隊優化功能、支援行銷團隊制定精準策略。 整合生成式 AI 應用: 導入並開發生成式 AI 功能，例如自動化產出運動新聞與球員動態，豐富產品內容。 提升內部數據工作流程效率: 運用 AI 技術優化資料處理、分析與建模的流程，提升團隊整體開發效率。

At SWAG Live's data team, our mission is to democratize data by building a self-service data platform. We aim to empower internal teams to access, interpret, and derive valuable insights from data effectively.As a Data Scientist in this role, you will collaborate with a multidisciplinary team of engineers and analysts to tackle diverse challenges using quantitative techniques such as statistical analysis and machine learning. You will work with large, complex event-based datasets, conduct exploratory data analysis (EDA), define requirements, and develop deploy models. We are particularly seeking a data scientist with experience in building customized recommendation models and a strong interest in product-focused machine learning development. Responsibilities Leverage state-of-the-art algorithms to build fully customized recommenders and other growth models.Design, deploy and maintain all components necessary for modeling, including feature engineering, automatic model training tuning and engineering toolchains.Create a comprehensive monitoring framework to evaluate model performance and provide actionable insights to drive business growth, focusing on awareness conversion and transactions.Understand stakeholder business requirements and design end-to-end machine learning/AI solutions that are effective, practical, and robust in addressing business challenges.Collaborate closely with data engineers and backend engineers to develop scalable systems.Communicate efficiently with cross-functional teams, promote the implementation of strategic applications, and drive continuous optimization.

WorldQuant develops and deploys systematic financial strategies across a broad range of asset classes and global markets. We seek to produce high-quality predictive signals (alphas) through our proprietary research platform to employ financial strategies focused on market inefficiencies. Our teams work collaboratively to drive the production of alphas and financial strategies – the foundation of a balanced, global investment platform. WorldQuant is built on a culture that pairs academic sensibility with accountability for results. Employees are encouraged to think openly about problems, balancing intellectualism and practicality. Excellent ideas come from anyone, anywhere. Employees are encouraged to challenge conventional thinking and possess an attitude of continuous improvement. Our goal is to hire the best and the brightest. We value intellectual horsepower first and foremost, and people who demonstrate an outstanding talent. There is no roadmap to future success, so we need people who can help us build it. The Role: We are seeking an exceptionally talented data scientist with strong modeling and programming skills to join our team. In this role, you will work closely with data science team and technologists across the firm to develop appropriate features and metrics for data processing. Perform analysis and generate models of financial datasets using machine learning techniques Process, clean and verify the integrity of unstructured data and turn data into valuable insights Develop and create data that seek to predict the movement of financial market Transfer data into internal infrastructure applying variety of algorithmic techniques What You’ll Bring: Have a Master’s degree or higher from a leading university in Computer Science, Electrical Engineering or other related areas Good academic record Familiar with modeling, data structures, algorithms and optimizations Strong knowledge of machine/deep learning algorithms Proficient in programming languages of both C++ and Python Possess good communication and presentation skills in English Ability to work independently and as member of a team Research scientist mindset: deep thinker, creative, strong work ethic, persevering, smart a self-starter Detail oriented and capable of multitasking and delivering in fast-paced work environment As a plus: While not mandatory, a strong interest in financial markets will definitely be beneficial Participant of ACM-ICPC By submitting this application, you acknowledge and consent to terms of the WorldQuant Privacy Policy. The privacy policy offers an explanation of how and why your data will be collected, how it will be used and disclosed, how it will be retained and secured, and what legal rights are associated with that data (including the rights of access, correction, and deletion). The policy also describes legal and contractual limitations on these rights. The specific rights and obligations of individuals living and working in different areas may vary by jurisdiction. Copyright © 2025 WorldQuant, LLC. All Rights Reserved.WorldQuant is an equal opportunity employer and does not discriminate in hiring on the basis of race, color, creed, religion, sex, sexual orientation or preference, age, marital status, citizenship, national origin, disability, military status, genetic predisposition or carrier status, or any other protected characteristic as established by applicable law.

・負責收集、清理、管理平台內外部數據，確保資料完整與正確，打造可供分析使用的數據集・監控數據質量與資料庫模型，持續優化數據處理流程・分析用戶行為（活躍、留存、付費）、市場活動成效及用戶來源渠道・應用統計、ML/DL 和生成式 AI 技術來建立使用者分類、詐欺偵測、情緒分析和其他目標的功能・以數據支持產品優化，協助設計及分析A/B測試・與其他產品開發團隊合作，了解他們的業務需求，如潛在用戶名單、用戶風險分析，制定並完成端到端分析，包括資料收集、分析、持續擴展交付和演示・使用Tableau/Power BI設計並維護BI報表，推動數據自助化・結合業界Knowhow與指標洞察，提出實際可行的解決方案

Mô tả công việcBuilding Machine Learning models using your core expertise;Collaborate with Product and Business to define the Machine Learning product, focus on Fraud/Risk management and Financial Services;Collecting, cleaning, preparing data at large scale for modeling;Adding new features, exploring new approaches to keep pushing the model performance;Participating in productionizing Machine Learning models for live production;Designing, conducting A/B tests and analyzing the results for experiment insights;Building pipelines for continuously validating and updating models.Yêu cầu công việc3+ years working experience with 2 years hands-on with ML, or 2+ years with PhD degree;Good understanding of mathematical foundations of Machine Learning algorithms;Have practical experience in applying Machine Learning in Fraud/Risk management, credit scoring or user behavior analysis;A builder. You go the extra mile to bring your prototypes to production;Strong product ownership. You take a high responsibility for what you build. You keep a high bar for product quality;Strong collaboration skills. You reach out to help other team members; Familiar with using genAI in analytics/modeling and coding;Experience with financial service models is a plus.

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.The Principal Data Scientist is the technical lead for the data science capability within the Data Analytics function. This role is responsible for the design, delivery, and governance of advanced analytical solutions that drive value across Marketing, Commercial, and CX.You will ensure that all data science initiatives are commercially aligned, technically robust, and integrated into the broader data estate. You will act as the technical lead for the data science roadmap, providing expertise to both direct reports and engineering teams to deliver end-to-end data products.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:Advanced Customer Marketing ScienceMarketing Effectiveness: Lead the end-to-end development of internal Marketing Mix Modelling and Multi-Touch Attribution frameworks to optimise global media investment and channel performance.Customer Behavioural Modelling: Oversee the development of predictive models such as churn, lifetime value, and propensity, ensuring these are operationalised within the Customer Data Platform.Strategic Segmentation: Design complex customer attributes and segments that enable high-precision personalisation across B2B and B2C commercial journeys.Decision Science: Lead the technical implementation of recommendation engines and next-best-action logic to automate and improve commercial decision-making. AI Technical GovernanceScientific Accountability: Act as the technical auditor for AI and machine learning outputs. You will be responsible for the scientific integrity of models, ensuring that LLM outputs and predictive insights are governed by rigorous statistical validation before they influence commercial decision-making.Consolidation of Distributed AI: Lead the technical standardisation of distributed and siloed AI initiatives. You will define the unified framework that ensures business-driven POCs and products are built as integrated, reusable assets rather than fragmented one-off scripts.Logic Standardisation: Bridge the gap between IT infrastructure and business science. While engineering teams provide the plumbing, you will own the brain, defining and enforcing consistent commercial logic and data definitions across conversational AI products in Marketing, Commercial and CX.Architectural Guardrails: Establish the standards for model reproducibility and explainability, ensuring that our insight-to-value automation remains transparent, compliant, and free from mathematical drift.  Leadership Strategic PartnershipStrategic Technical Deputy: Serve as the technical right hand to the Head of Data Analytics. You will own the AI Data Science roadmap, supporting Head to ensure strategic stakeholder alignment and business value delivery.Architectural Oversight: Provide the high-level technical direction for the engineering teams across Marketing, Commercial and CX. You will ensure that Snowflake architectures are optimised for cross-functional science, preventing the accumulation of tactical debt.Complexity Management: Navigate the interdependencies between business units. You will ensure that analytical assets built for one function (e.g. Marketing) can directly accelerate the delivery of others (e.g. CX), creating a unified logic across the estate.Capability Elevation: Provide technical leadership and coaching to the Lead Data Scientist, from a focus on technical model production to end-to-end commercial solutioningKey QualificationsFor this role, we need a blend of an Engineer’s discipline and a Statistician’s mind.Education Experience:Academic Foundation: Master’s or PhD in a quantitative field (Statistics, Mathematics, Computer Science, Economics).Advanced Statistical Mastery: Deep expertise in causal inference, experimental design, and Bayesian statistics. Proven track record in architecting and implementing internal MMM and MTA models.Modern AI Governance Architecture: Demonstrable expertise in Agentic AI architecture and the technical standardisation of distributed LLM products.Data Science Architecture: High proficiency in Python and SQL, with experience designing scalable data science logic and shared assets within a Snowflake ecosystem.Technical Accountability: Expertise in establishing MLOps, model reproducibility, and explainable AI frameworks to act as the final technical sign-off for model integrity.Technical Advocacy: Experience providing the scientific validation and technical evidence required to support department leadership in defending data science outputs to non-technical stakeholders.Strategic Technical Leadership: Experience acting as a technical deputy to leadership, with a track record of coaching teams to navigate complex, cross-functional interdependencies.Scientific Translation: Ability to map high-level commercial objectives to technical specifications, ensuring that data science products are architected to deliver measurable business value.Requirements Engineering: Excellence in translating ambiguous business challenges into structured, scalable technical specifications.Insight Partnership: Ability to collaborate with Tableau developers to ensure complex scientific outputs are translated into actionable visualisations.Corporate Agility: Ability to work autonomously in a fast-paced, matrixed environment, maintaining a Hungry and Humble attitude toward innovation and change.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.

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 Role:The Marketing Data Scientist, Logitech For Business, is a strategic, highly analytical individual contributor responsible for transforming complex marketing data into actionable insights that drive growth and optimize performance across global business markets. This role will be critical in elevating the analytics maturity of the marketing organization and will work in close partnership with the Marketing Analytics Insights Manager to deliver robust modeling, forecasting, and reporting solutions that support data-driven decision-making. The ideal candidate will bring proven experience in marketing analytics or data science within B2B organizations, coupled with deep technical skills and business acumen.Your Contribution:Be Yourself. Be Open. Stay Hungry and Humble. Collaborate. Challenge. Decide and just Do. Share our passion for Equality and the Environment. These are the behaviors you’ll need for success at Logitech. In this role you will:Advanced Analytics ModelingDevelop and implement statistical models, machine learning algorithms, and attribution analyses to measure the impact of multi-channel B2B marketing campaigns.Optimize lead scoring, segmentation, and customer journey mapping using predictive analytics.Data Management IntegrationDesign and automate data integration pipelines from disparate marketing and sales systems (e.g., CRM, MAP, web analytics).Ensure data quality, governance, and integrity throughout all analytics processes.Performance Measurement ReportingCreate visualizations and dashboards. Partner with the Marketing Analytics and Insights manager to create executive-ready reports to communicate insights to marketing leadership and stakeholders.Define and track KPIs for marketing engagement, pipeline contribution, and ROI.Experimentation OptimizationLead A/B testing, multivariate testing, and other experimental approaches to optimize campaigns and processes.Provide recommendations for continuous improvement based on data findings.Collaboration Stakeholder EngagementPartner closely with the Marketing Analytics Insights Manager to align analytics initiatives with business goals.Your Skills:For consideration, you must bring the following skills and behaviors to our team:Bachelor’s or Master’s degree in Data Science, Statistics, Computer Science, Mathematics, Marketing Analytics, or related fieldProven experience in marketing analytics, data science, or a related field within a B2B contextDeep knowledge of B2B marketing and sales funnels (lead acquisition through pipeline and revenue)Demonstrated expertise in building and deploying statistical models and predictive analyticsAdvanced SQL skills and experience working with large, complex datasetsProficiency in data visualization tools (e.g., Tableau, Power BI)Strong communication skills—capable of translating complex data into clear business insightsExperience with A/B testing, causal inference, and marketing mix modelingAbility to work independently while building strong collaborative relationships across functionsClose attention to detail, strong project management, and time management skillsAnalytics Statistical Tools: Python (pandas, scikit-learn, numpy), R, SQLData Visualization: Tableau, Power BI, or similar platformsData Management: Snowflake, BigQuery, Redshift, or equivalent cloud data warehousesMarketing Technology: Salesforce, Marketo, Eloqua, HubSpot, or comparable CRM and marketing automation platforms. Experience with Marketo Measure (formerly Bizible) a huge plus! Experimentation: Google Optimize, Adobe Target, or similar A/B testing toolsOther: Git, Jupyter Notebook, Excel (advanced analysis)#LI-MT1Across 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 in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, a related quantitative field, or equivalent practical experience. 8 years of experience using analytics to solve product or business problems, performing statistical analysis, and coding (e.g., Python, R, SQL), or 5 years of experience with a Master's degree. Preferred qualifications: Master'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). Experience in product analytics within payments, e-commerce, or financial services. Ability to take initiative in unstructured environments with a bias for action and sharp attention to detail. 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. As a Product Data Scientist for FOP Optimization, you will shape Payments products and solutions, helping our leaders make data-driven decisions. You will lead a critical part of the payments routing infrastructure, Smart Router, that utilizes machine learning and AI to process first-party transactions across Play, YouTube, Ads, and more. You will drive analytics for form of payment (FOP) optimization, building on success metrics, driving insights, and driving global launches. You will also play a critical role in our interactions on B2C analytics with Play and YouTube to optimize buyflows, purchase readiness, conversion, and UI on these critical Google products.Responsibilities Play a critical role in shaping the future of Google Payments by leveraging data and analytics to drive decisions, influencing strategy, and creating business impact across the organization. Identify and solve ambiguous, high-stakes problems, transforming data into clear, actionable insights that directly influence leadership decisions (e.g., VPs and directors). Lead complex projects that combine analytical precision with organizational strategy, delivering clear and actionable insights that inform tangible business decisions. Contribute to the development and alignment of team OKRs and analytics strategy to ensure they support broader product and business goals across the Payments organization. Collaborate cross-functionally with product, engineering, and operations teams to define key metrics and support data-driven decision making. 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.

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.Hybrid role - 2 to 3 days a week on siteRole PurposeThe Digital Marketing Data Scientist / Marketing Effectiveness Lead will advance Logitech’s marketing science capabilities within the Digital Marketing Center of Excellence (COE).This role will focus on developing advanced measurement methodologies, predictive analytics, and marketing effectiveness models across Paid Media, Organic Channels, Social Media, Creators ecosystems, and Software Marketing initiatives.Working closely with the Head of Digital Marketing Analytics, this role will help the organization evolve from descriptive reporting toward causal measurement, experimentation, and AI-powered marketing insights, enabling more effective marketing investment decisions across paid media and organic growth channels.Key ResponsibilitiesMarketing Effectiveness Attribution ModelingDevelop and maintain advanced marketing measurement methodologies including Marketing Mix Modeling (MMM), incrementality testing, and causal inference frameworks.Build attribution models capturing the combined impact of paid media, organic marketing channels, creators ecosystems, and software growth initiatives.Support measurement of product-led growth signals including software adoption, engagement, retention, and lifecycle marketing performance. Advanced Analytics Predictive ModelingBuild predictive models to forecast marketing performance across paid and organic channels.Identify key drivers of marketing performance across search, social, creators ecosystems, SEO, and software adoption signals.Develop analytical models supporting budget allocation, media mix optimization, and marketing ROI forecasting. Experimentation Testing FrameworksDesign and implement experimentation methodologies to evaluate marketing initiatives.Partner with Paid Media, Social Media, Creators, and Organic teams to run incrementality tests and controlled experiments.Establish best practices for testing creative formats, organic content strategies, creators programs, and channel investment strategies. AI-Driven Insights AutomationLeverage machine learning and AI tools to automate insights generation and anomaly detection.Develop frameworks identifying performance trends across paid, organic, and earned.Support the evolution of AI-powered analytics capabilities within the COE. Emerging Channel MeasurementDevelop measurement models for AI discovery channels and generative search platforms.Analyze performance signals related to LLMO / AEO visibility and AI-generated traffic sources. Data Integration Analytics InfrastructureLeverage the Marketing Data Hub (Snowflake), Adverity ETL infrastructure, and Tableau dashboards to build scalable analytics solutions.Integrate datasets spanning paid media platforms, organic channels, creators platforms, web analytics, and software marketing analytics.Partner with Ad Tech and Digital Office teams to ensure high-quality data pipelines supporting analytical modeling. Strategic Insights CollaborationTranslate advanced analytical findings into actionable insights for marketing leaders.Partner with Business Groups, Regions, and Product teams to guide marketing investment and growth strategies.Support the Head of Digital Marketing Analytics and COE team members in building a data-driven marketing culture across the organization. Profile Requirements6–8 years experience in marketing analytics, marketing science, data science, or quantitative marketing roles.Strong expertise in marketing effectiveness measurement (MMM, incrementality testing, attribution modeling).Experience working with large marketing and product datasets.Strong programming skills (Python, R, SQL or equivalent).Familiarity with digital marketing ecosystems including paid media platforms, organic marketing channels, creators ecosystems, and product analytics tools.Experience working with data warehouses and BI platforms (Snowflake, Tableau or equivalent).Ability to translate advanced analytical models into clear and actionable business recommendations.Comfortable working in a global, cross-functional environment spanning marketing, analytics, and technology teams.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.