Cake Job Search

Lead / Senior Data Scientist responsible for driving data science initiatives focused on recommender systems and user engagement, with a strong emphasis on marketing and promotion platforms.Mô tả công việcBuild and improve Machine Learning models to power recommender systems, personalization, and user engagement use cases.Work closely with Product and Business teams to define Machine Learning problems and translate them into scalable data products.Collect, clean, and prepare large-scale datasets for modeling and analysis.Design and engineer features, experiment with new approaches, and continuously improve model performance.Deploy and productionize Machine Learning models in live systems with reliability and scalability in mind.Design, run, and analyze A/B tests to evaluate the impact of the model and generate actionable insights.Build and maintain pipelines for continuous model validation, monitoring, and retraining.Yêu cầu công việcAt least 5 years of working experience with 3 years of hands-on Machine Learning experience, or 2+ years with a PhD in a relevant field.Strong understanding of the mathematical foundations behind Machine Learning algorithms.Proven experience applying Machine Learning to personalization, recommender systems, user behavior analysis, or credit scoring.A strong builder mindset with the ability to take models from prototype to production.High product ownership with a strong sense of responsibility for quality, impact, and long-term maintainability.Strong collaboration skills and willingness to actively support and mentor team members.Experience with credit scoring or financial services models is a plus.

Astera Labs (NASDAQ: ALAB) provides rack-scale AI infrastructure through purpose-built connectivity solutions. By collaborating with hyperscalers and ecosystem partners, Astera Labs enables organizations to unlock the full potential of modern AI. Astera Labs’ Intelligent Connectivity Platform integrates CXL®, Ethernet, NVLink, PCIe®, and UALink™ semiconductor-based technologies with the company’s COSMOS software suite to unify diverse components into cohesive, flexible systems that deliver end-to-end scale-up, and scale-out connectivity. The company’s custom connectivity solutions business complements its standards-based portfolio, enabling customers to deploy tailored architectures to meet their unique infrastructure requirements. Discover more at www.asteralabs.com.Job Description Astera labs is seeking a skilled and motivated Data Scientist. This individual will play a pivotal role in identifying key data points for collection, developing strategies to accumulate data and deriving actionable insights an anomaly based on a solid foundation of relevant know-how. Also, will also be responsible for creating, testing, and deploying scripts and methods for data collection and analysis to support decision-making. The Engineer will collaborate with cross-functional teams to identify critical data sources to determine the most effective data collection strategies, will develop automated and scalable data collection pipelines, will ensure data quality, integrity, and consistency across all sources and may use AI techniques to refine the results toward failures predictions. Basic Qualifications Bachelor’s degree in computer science, Data Science, Engineering, Mathematics, or a related field. Advanced degrees in data science or Machine learning / AI - Advance. Proficiency in programming languages such as Python, R, or MATLAB. Strong understanding of data manipulation and analysis tools (e.g., Pandas, NumPy, SQL). Understanding of high speed interfaces such as Ethernet, PCI-E , WiFi. Experience with data visualization tools such as Tableau, Matplotlib, Graphana. Strong analytical and critical-thinking skills to identify patterns and outliers. Customer-obsession, Think and act with the customer in mind! Goal-driven, Self-motivated, be able to work independently and with teams with people around the globe. Entrepreneurial, open-minded behavior and can-do attitude. Required Experience Experience with data manipulation and analysis tools (e.g., Pandas, NumPy, SQL). Machine learning and AI techniques and frameworks (e.g., TensorFlow, Scikit-learn). Proven ability to manage multiple tasks and meet deadlines. Preferred Experience Embedded Firmware development with C-language, scripting with Python or other equivalent programming languages. Master’s degree in a relevant field. Experience with cloud platforms (e.g., AWS, Azure, GCP) for data storage and processing. Familiarity with big data technologies (e.g., Hadoop, Spark). Knowledge of engineering design tools and processes. We know that creativity and innovation happen more often when teams include diverse ideas, backgrounds, and experiences, and we actively encourage everyone with relevant experience to apply, including people of color, LGBTQ+ and non-binary people, veterans, parents, and individuals with disabilities.

Note: By applying to this position you will have an opportunity to share your preferred working location from the following: Bengaluru, Karnataka, India; Hyderabad, Telangana, India.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. 3 years of experience as a people manager within a technical leadership role. Preferred qualifications: Master's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field. 12 years of experience using analytics to solve product or business problems, performing statistical analysis, and coding (e.g., Python, R, SQL). 4 years of experience as a people manager within a technical leadership role. Ability to take initiatives and address ambiguous questions. Excellent data visualization skills. 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. In this role, you will drive our initiatives to enable global operational excellence, advise the data-driven strategy for Geo’s critical emerging markets and provide insights that touch user journeys across the whole spectrum of the Maps space, from helping users find the best restaurant with a voice query to enable companies leveraging our APIs to service millions of people. You will manage a high-impact team of analysts to provide the data foundation necessary to steer Geo’s strategy across multiple organizational boundaries and large variety of executive stakeholders answering questions.Responsibilities Partner with stakeholders across multiple functions (Product Management/Program Management/Software Engineering/UX) to create data driven strategies accounting for a variety of users and requirements across geospatial use cases. Prioritize and communicate user needs, making recommendations and driving implementation for product or process changes to identify top challenges and key strategic growth opportunities. Perform large-scale data analysis, modeling, time series decomposition and more to identify opportunities for improvement and measure shifts in Engineering and Operations deployments worth $400M. Oversee the development of data layers, metrics and modeling to guide Geo Operations' AI Transformation. Expand investigative frameworks to synthesize consumer insights, developer perspectives, and routing quality to create holistic, end-to-end narratives for strategic Maps markets. Execute advanced attribution modeling to quantify the direct impact of data quality improvements on product growth, user reach, and engagement. 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 work experience using analytics to solve product or business problems, performing statistical analysis, and coding (e.g., Python, R, SQL) (or 8 years of work experience with a Master's degree). 8 years of experience with data science and analytics in a technology or supply chain company. Experience in data model and data insight transformation. Preferred qualifications: Master's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field. 12 years of work experience using analytics to solve product or business problems, performing statistical analysis, and coding (e.g., Python, R, SQL). 4 years of experience as a people manager within a technical leadership role. Experience with data, metrics, analysis and trends, with the knowledge of measurement, statistics and program evaluation. Ability to synthesize multiple data points, points of view and analyses into actionable and meaningful insights. 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 mission of Cloud Supply Chain Data (CSCD) Data Science and Product team is to build productivity and data products, develop AI/ML/statistical models and provide prescriptive insights to help CSCD define and achieve business goals. We help make Google Cloud supply chain and Data Centers by enabling data-informed decision making and product innovation.The AI and Infrastructure team is redefining what’s possible. We empower Google customers with breakthrough capabilities and insights by delivering AI and Infrastructure at unparalleled scale, efficiency, reliability and velocity. Our customers include Googlers, Google Cloud customers, and billions of Google users worldwide.We're the driving force behind Google's groundbreaking innovations, empowering the development of our cutting-edge AI models, delivering unparalleled computing power to global services, and providing the essential platforms that enable developers to build the future. From software to hardware our teams are shaping the future of world-leading hyperscale computing, with key teams working on the development of our TPUs, Vertex AI for Google Cloud, Google Global Networking, Data Center operations, systems research, and much more.Responsibilities Manage Bengaluru Center of Excellence for Cloud Supply Chain and Operations, Data Science and Product team. Lead a portfolio of programs in developing ML/Statistical models, conducting diagnostic analytics research, crafting prescriptive insights. Guide problem framing, metrics development, data extraction and manipulation, visualization, and story telling for the team. Provide thought leadership through proactive and strategic contributions (e.g., suggests new analyses, infrastructure or experiments to drive improvements in the business). Oversee the integration of cross-functional and cross-organizational project/process timelines, develop process improvements and recommendations, and define operational goals and objectives. 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.

About BTSE:彼特思方舟 is a specialized service provider dedicated to delivering a full spectrum of front-office and back-office support solutions, each of which are tailored to the unique needs of global financial technology firms. 彼特思方舟 is engaged by BTSE Group to offer several key positions, enabling the delivery of cutting-edge technology and tailored solutions that meet the evolving demands of the fintech industry in a competitive global market.About the Role:We are seeking a dynamic and strategic Data Product Manager to bridge the gap between product innovation and data-driven insights. This role is responsible for defining and executing a data strategy that enhances our product offerings, optimizes decision-making, and drives business growth. You will work closely with cross-functional teams—including product, engineering, data science, and analytics—to ensure that data is at the heart of our product strategy and execution.Responsibilities:Understand product values and feature details to translate them into precise data requirements.Prioritize the product-related data requests backlog to align with product strategic objectives.Address gaps in our data ecosystem by defining tracking specifications and ensuring successful implementation and launch.Comprehend the meaning of data and clearly explain its context and significance to the data team for effective analysis.Initiate data insight projects with the data team for internal sharing and continuous product improvement.Qualifications:3+ years of experiencein data, analytics, or a related roleExperience definingdata tracking / event specsand coordinating with engineering or data teamsComfortable definingdata requirements, and able to structure dashboards and metrics based on product or business needsFamiliar withtrading products and workflows(e.g. stocks, futures, or crypto), with enough hands-on exposure to understand user behavior and data needsAble tocommunicate clearlywith product, engineering, and data teamsBonus Points:Experience in the blockchain or financial technology industry.Background in data analysis or data science.Perks Benefits:Competitive salary and benefits package.Opportunity to work in a fast-paced and innovative environment.Be part of a growing and dynamic team.Make a real impact on the company's success.Various team building programs and company events.Comprehensive healthcare schemes for employees and dependants.And many more! Apply and let us tell you more!#LI-JY1

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.

Responsibilities Lead the design and development of end-to-end data science projects, from business problem understanding to model deployment and monitoring.Collaborate with domain experts and cross-functional teams to translate business goals into goal-driven autonomous agent workflows.Design and implement robust RAG (Retrieval-Augmented Generation) pipelines to enhance the performance of large language model (LLM) applications.Prototype and deploy multi-agent LLM systems for planning, reasoning, and task orchestration. Build and deploy machine learning models for use cases such as recommendation systems, NLP, time-series forecasting, and computer vision.

公司介紹 這是一家深耕台灣市場、具高度用戶滲透率的 FinTech 科技公司，長期處於高流量、高交易頻率的業務場景。產品服務已融入日常生活與金融行為，資料規模與複雜度持續成長。 目前公司正進入 數據基礎建設與治理升級的關鍵階段，高層明確將「數據驅動決策」視為下一階段成長核心，並投入資源打造更穩定、可擴展的資料平台，讓數據真正成為產品與營運的決策引擎。 這個角色將站在 公司級數據戰略中心，不只是管理團隊，而是實際參與並影響整體商業方向。 工作內容 帶領資料應用部門（資料工程、資料分析、BI / Data Science 團隊），管理約 5–10 位成員 規劃並推動 公司級 Data Platform（Data Lake / DWH / ETL / Streaming） 與工程與系統架構團隊協作，確保資料系統的 穩定性、可用性與擴展性 審視並優化資料流、事件系統、Schema 與整體資料架構設計 建立 資料治理、品質控管、權限與統計口徑制度 建構指標、Dashboard 與分析框架，支援 產品、營運、行銷與管理決策 推動 A/B Test、數據實驗與行為分析，讓決策有數據依據 作為跨部門橋樑，協調技術與商業需求，推動策略落地 使用的技術 Data Platform：Data Lake、Data Warehouse、ETL / ELT、Streaming Big Data / Pipeline：Spark、Kafka、Airflow Data Ops：Pipeline 監控、版本控管、CI/CD Cloud / Hybrid：BigQuery、Snowflake（地端為主、雲端為輔） BI / Analytics：指標設計、Dashboard、實驗分析

Minimum qualifications: Bachelor's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field. 2 years of work experience with analysis applications (extracting insights, performing statistical analysis, or solving business problems), and coding (Python, R, SQL) (or work experience with a Master's degree). Preferred qualifications: Master's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field. 3 years of work experience with analysis applications (extracting insights, performing statistical analysis, or solving business problems), and coding (Python, R, SQL). Understanding of digital advertising measurement concepts, including attribution modeling, incrementality testing, and media mix modeling (MMM). Excellent communication and presentation skills with the ability to influence stakeholders. 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.Responsibilities Execute defined, moderately difficult investigative tasks under guidance from the manager or executive team member/TL. Execute end-to-end analysis with minimal guidance. Manage workload to reflect the priorities set by the team, work towards a timeline, and communicate slippage. Handle data communication, limits, and importance. Collaborate with Product Managers, Engineers, and Research Scientists to define and track key performance indicators (KPIs) for Google Ads measurement products. Select appropriate approaches from clear options to address technical challenges under guidance from managers or executive team members.  Conduct in-depth analysis of large datasets to identify trends, patterns, and insights that inform product strategy and development. Communicate data and analysis in a clear and concise manner to various stakeholders, including product leadership, engineering teams, and business partners. 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, Mathematics, a related field, or equivalent practical experience. 1 year of experience with data processing software (e.g., Hadoop, Spark, Pig, Hive) and algorithms (e.g., MapReduce, Flume). Experience with database administration techniques or data engineering, as well as writing software in Java, C++, Python, Go, or JavaScript. Experience managing client-facing projects, troubleshooting technical issues, and working with Engineering and Sales Services teams. Preferred qualifications: Experience working with data warehouses, including data warehouse technical architectures, infrastructure components, ETL/ELT, and reporting/analytic tools and environments. Experience working with Big Data, information retrieval, data mining, or machine learning. Experience in building multi-tier high availability applications with modern web technologies (e.g., NoSQL, MongoDB, SparkML, TensorFlow). Experience architecting, developing software, or internet scale production-grade Big Data solutions in virtualized environments. About the jobAs a Data Engineer for the Enterprise Platforms team, you will play a vital role in building and maintaining the data infrastructure that fuels our product strategy. You will design, develop, and optimize data pipelines, ensuring data quality and accessibility for advanced analytics. Your technical expertise will enable the product team to leverage data-driven insights to optimize product feature adoption and performance and measure the impact of strategic initiatives. To accelerate the growth and market leadership of Enterprise Buying Platforms (DV360 and SA360), you will answer critical business questions and deliver actionable, data-driven insights that inform product and commercial strategy. The Enterprise Platform Data Science team provides quantitative support, market understanding and a strategic perspective to our partners throughout the organization, in close collaboration with the Ads Commerce Finance team.Google Ads is helping power the open internet with the best technology that connects and creates value for people, publishers, advertisers, and Google. We’re made up of multiple teams, building Google’s Advertising products including search, display, shopping, travel and video advertising, as well as analytics. Our teams create trusted experiences between people and businesses with useful ads. We help grow businesses of all sizes from small businesses, to large brands, to YouTube creators, with effective advertiser tools that deliver measurable results. We also enable Google to engage with customers at scale. Responsibilities Create and deliver best practice recommendations, tutorials, blog articles, sample code, and technical presentations, tailoring approach and messaging to varied levels of business and technical stakeholders. Design, develop, and maintain scalable and reliable data pipelines to collect, process, and store data from various data sources. Implement robust data quality checks and monitoring to ensure data accuracy and integrity. Collaborate with cross-functional teams (data science, engineering, product managers, sales and finance) to understand data requirements and deliver impactful data solutions. Optimize data infrastructure for performance, efficiency, and scalability to meet evolving business needs. 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.