Data Engineer jobs at Adobe - 1572 jobs

A leading aerospace and defense technology company is seeking a full-time Corporate Software Engineering Director 1 in Redondo Beach, CA. This role involves leading the enterprise-wide Software Engineering Council and establishing effective software processes and governance across the organization. The ideal candidate will have significant software engineering and management experience, a strong educational background in STEM, and must hold a current Secret security clearance. This position offers a competitive salary range between $193,800 and $336,500, reflecting the candidate's experience and responsibilities. #J-18808-Ljbffr

A leading defense technology company is looking for a Corporate Software Engineering Director 1 in San Diego, CA. This role involves shaping the vision and strategy of software engineering at the corporate level, leading a centralized function, and driving continuous improvement initiatives. Candidates must have extensive experience in software management and a current DOD Secret clearance. The position offers a competitive salary range from $193,800 to $336,500, alongside comprehensive benefits. #J-18808-Ljbffr

A leading defense and aerospace company is seeking a full-time Corporate Software Engineering Director 1 to lead their Software Engineering function at the corporate level. This role involves establishing a centralized software function, spearheading strategic initiatives, and managing cross-sector development programs. Candidates must have a STEM degree, extensive experience in software engineering management, and a current Secret clearance. The position is based in El Segundo, California, and requires occasional travel. #J-18808-Ljbffr

Push the boundaries of tech. In your sweatpants. We're looking for an experienced Senior Data Engineer to help us change how the world works. Here, you'll be part of our Data Engineering & Analytics team, supporting cross-functional groups around the world. The right candidate will develop, review, and maintain data infrastructure and various data flows. You will also develop means to ensure continuous data validation and telemetry for all data processes. The top creative and technical minds could work anywhere. So why are so many of them choosing Corel? Here are three reasons: This is the moment. It's an exciting time at Corel, with new leadership, a refreshed brand, and a whole new approach to changing the way the world works. We're at the forefront of a movement, and we want you to ride this wave with us. We want you to be you . Too often, companies tell you about their culture and then expect you to fit it. Our culture is built from the people who work here. We want you to feel safe to be who you are, take risks, and show us what you've got. It's your world. We know you have a life. We want to be part of it, but not all of it. At Corel, we're serious about empowering people to work when, how, and where they want. Couch? Sweatpants? Cool with us. We believe that happy employees mean happy customers. That's why we hire amazing people and get out of their way. Sound good so far? Awesome. Let's talk more about the Senior Data Engineer role and see if we're destined to be together. As a Senior Data Engineer, you will: Design, develop and implement large scale, high-volume, high-performance data infrastructure and pipelines for Data Lake and Data Warehouse Build and implement ETL frameworks to improve code quality and reliability Build and enforce common design patterns to increase code maintainability Ensure accuracy and consistency of data processing, results, and reporting Design cloud-native data pipelines, automation routines, and database schemas that can be leveraged to do predictive and prescriptive machine learning Communicate ideas clearly, both verbally and through concise documentation, to various business sponsors, business analysts and technical resources Guide and mentor other Data Engineers as a technical owner of parts of the data platform What YOU bring to the team: Expert knowledge of Python Expert knowledge of SQL Experience with DevOps mode of work 7+ years of professional experience 5+ years of experience working in data engineering, business intelligence, or a similar role 5+ years of experience in ETL orchestration and workflow management tools like Airflow, flink, etc. using AWS/GCP 3+ years of experience with the distributed data processing tools like Spark, Presto, etc. and streaming technologies such as Kafka/Flink 3+ years of experience with SnowFlake (preferred) or another big data database platform 3+ years of experience with cloud service providers: Amazon AWS (preferred), or one of the other major clouds Expertise with containerization orchestration engines (Kubernetes) MS in Computer Science, Software Engineering, or relevant field preferred, BS in one of same fields acceptable Our Team: Corel features award-winning solutions that have helped millions of users for 40 years (can you believe it?!). We offer a fully remote workspace, and we mean it. There is no pressure to work in an office whatsoever. Hours are flexible! You've worked hard to build your life, and we don't want you to give it up for work. Our team is growing fast, and there's a ton of energy and a lot of really smart, motivated, fun people ready to welcome you in. What are you waiting for? Apply now! We can't wait to meet you. (FYI, we're lucky to have a lot of interest and we so appreciate your application, though please note that we'll only contact you if you've been selected for an interview.) About Corel Corel is a beloved and trusted industry titan fueled by make-everything-easier flexibility. With a 40-year legacy of innovation, we understand where you've been, and we're uniquely equipped to get you where you want to be. Our comprehensive collection of creative, collaborative, and productivity solutions propel your teams on their journey. From meeting your deadlines to realizing your dreams, Corel empowers all you do. Our products enable millions of connected knowledge workers around the world to do great work faster. Our success is driven by an unwavering commitment to deliver a broad portfolio of innovative applications - including CorelDRAW , MindManager , Parallels , and WinZip - to inspire users and help them achieve their goals. It is our policy and practice to offer equal employment opportunities to all qualified applicants and employees without regard to race, color, age, religion, national origin, sex, political affiliation, sexual orientation, marital status, disability, veteran status, genetics, or any other protected characteristic. Corel is committed to an inclusive, barrier-free recruitment and selection process and work environment. If you are contacted for a job opportunity, please advise us of any accommodation that are required. Appropriate accommodation will be provided upon request as required by Federal and Provincial regulations and Company Policy. Any information received relating to accommodation will be treated as confidential. #LI-Remote

Our Company Changing the world through digital experiences is what Adobe's all about. We give everyone-from emerging artists to global brands-everything they need to design and deliver exceptional digital experiences! We're passionate about empowering people to create beautiful and powerful images, videos, and apps, and transform how companies interact with customers across every screen. We're on a mission to hire the very best and are committed to creating exceptional employee experiences where everyone is respected and has access to equal opportunity. We realize that new ideas can come from everywhere in the organization, and we know the next big idea could be yours! The Challenge: We are a dynamic detailed oriented finance data engineering team seeking a collaborative partner to help drive further excellence in the world of finance. We strive to delight our clients with the best data while ensuring cohesive solutions. The Financial Data Engineer performs a wide range of job duties applying technical know-how and develop an analytics product that will generate insights into financial indicators and customer journey! Maintains a very hands-on focus for technology matters combined with an affinity for solving complex technical and business issues, enabling tools for self-service financial analyst community and delivering projects on time with very high quality! Who you are: * You work independently, prioritize individual workload, solve and remedy problems under pressing deadlines * You exercise good judgment and a pragmatic approach to delivering solutions that optimizes architecture activities across company needs, business constraints and varying technological realities * Document and demonstrate solutions by developing design documentation, code comments, presentations and code execution. * You are customer service oriented Responsibilities: * Provide the creation of useful models to communicate current state, future state, and gap definitions in support of decision-making processes. * Consult in the refinement of existing models, adding new ideas to make the result more flexible and more tightly linked to current and expected requirements * Participates in project conceptual modeling, discovery processes, technical design/reviews, and project meetings in order to provide appropriate guidance that influences toward positive business outcomes. Qualifications: * 7+ years' experience with strong Python, SQL/PLSQL skills and technologies like Azure Databricks with enterprise data warehousing experience. * Strong data modeling and performance optimization skills. * Ability to design, develop, and migrate data analytics solutions by sourcing data from SAP HANA, SQL Server and other databases. * Experience working with analytics reporting for sales, bookings, finance, and subscription business areas. * Ability to design, develop, and test ETL solutions, including modeling data warehouse metadata and automating data loading processes. * Experience with Airflow or other ETL tools is a plus. * Experience with BI technologies like Tableau and PowerBI is a plus. * Experience monitoring, solving and tuning services/applications and operational expertise such as good problem solving skills, understanding of systems capacity, bottlenecks, and basics of memory, CPU, OS, storage, and networks. * Bachelor's degree or equivalent experience in computer science, Information Science, Information Technology or Engineering or a related Field Our compensation reflects the cost of labor across several U.S. geographic markets, and we pay differently based on those defined markets. The U.S. pay range for this position is $112,400 -- $226,550 annually. Pay within this range varies by work location and may also depend on job-related knowledge, skills, and experience. Your recruiter can share more about the specific salary range for the job location during the hiring process. In California, the pay range for this position is $156,500 - $226,550 At Adobe, for sales roles starting salaries are expressed as total target compensation (TTC = base + commission), and short-term incentives are in the form of sales commission plans. Non-sales roles starting salaries are expressed as base salary and short-term incentives are in the form of the Annual Incentive Plan (AIP). In addition, certain roles may be eligible for long-term incentives in the form of a new hire equity award. State-Specific Notices: California: Fair Chance Ordinances Adobe will consider qualified applicants with arrest or conviction records for employment in accordance with state and local laws and "fair chance" ordinances. Colorado: Application Window Notice If this role is open to hiring in Colorado (as listed on the job posting), the application window will remain open until at least the date and time stated above in Pacific Time, in compliance with Colorado pay transparency regulations. If this role does not have Colorado listed as a hiring location, no specific application window applies, and the posting may close at any time based on hiring needs. Massachusetts: Massachusetts Legal Notice It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability. Adobe is proud to be an Equal Employment Opportunity employer. We do not discriminate based on gender, race or color, ethnicity or national origin, age, disability, religion, sexual orientation, gender identity or expression, veteran status, or any other applicable characteristics protected by law. Learn more. Adobe aims to make Adobe.com accessible to any and all users. If you have a disability or special need that requires accommodation to navigate our website or complete the application process, email accommodations@adobe.com or call **************.

Minimum qualifications: Bachelor's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field. 5 years of experience with analysis applications (e.g., extracting insights, performing statistical analysis, or solving business problems), and coding (e.g., Python, R, SQL) or 2 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. 5 years of experience with analysis applications (e.g., extracting insights, performing statistical analysis, or solving business problems), and coding (e.g., Python, R, SQL). About the job Help 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. Measurement is a cornerstone of performance advertising, driving the majority of Google Ads business growth. Accurate and unbiased measurement empowers bidding engines to maximize advertiser Return On Investment (ROI), fostering growth for both advertisers and Google. The Product Analyst team applies advanced analytics to guide Google Ads strategy in this crucial area, ensuring that our advertising solutions effectively connect businesses with customers and deliver measurable results across our broad ad platforms. Users come first at Google. Nowhere is this more important than on our Advertising and Commerce team: we believe that ads and commercial information can be highly useful to our users if that information is relevant to what our users wish to find or do. Advertisers worldwide use Google Ads to promote their products; publishers use AdSense to serve relevant ads on their website; and business around the world use our products (like Google Shopping, and Google Wallet) to support their online businesses and bring users into their offline stores. We are constantly innovating to deliver the most effective advertising and commerce opportunities of tomorrow. The US base salary range for this full-time position is $132,000-$189,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process. Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google. Responsibilities Own the process of gathering, extracting, and compiling data across sources via relevant tools (e.g., SQL, R, Python). Format, re-structure, and validate data to ensure quality. Report Key Performance Indicators (KPIs) to support business reviews with cross-functional/organizational leadership team. Translate analysis results to business insights or product improvement opportunities. Provide analytical insights and recommendations to influence product feature development decisions, and with some guidance. Build and prototype analysis and business cases iteratively to provide insights at scale. Develop comprehensive knowledge of Google data structures and metrics. Execute defined, moderately difficult analytical tasks under guidance from the manager or executive team members/TL. For straightforward problems, execute end-to-end analysis with minimal guidance.

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. Experience building predictive or causal models to understand user behaviors (such as churn, loyalty, engagement, etc.). 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). About the job Google Pixel phones, watches, and earbuds showcase the best of Google's hardware and AI. We develop technologies to make user experiences faster, more powerful, and seamless including industry leading camera features powered by Google's expertise in Artificial Intelligence and Machine Learning. The Pixel Data Science team's mission is to power the growth and evolution of the Pixel ecosystem. We bridge data, analytics, and business strategy, acting as essential thought partners to product and strategy leaders within the centralized Devices and Services Strategy and Operations (StratOps) organization. By uncovering critical insights and developing data-driven solutions, we optimize performance, enhance user experiences, and help scale the Google Pixel business. In this role, you will provide business critical insights, leveraging data to influence the direction of products. Your work will directly contribute to key decisions and the overall success of the Pixel line.The US base salary range for this full-time position is $183,000-$271,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process. Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google. Responsibilities Perform analysis on key Pixel metrics utilizing advanced investigative tools (e.g., SQL, R, Python). Own and execute the full workstream for Pixel dashboards, including data engineering, dashboard design, metrics definition, and insights sharing. Own outcomes for projects by covering problem definition, metrics development, data extraction and manipulation, visualization, creation, and implementation of statistical models, and presentation to stakeholders. Develop solutions for ambiguous problems lacking clear precedent by framing hypotheses and providing recommendations that combine investigative and product-specific expertise. Liaise and align cross-functionally with Product Management, Marketing, Sales, and Executive leadership to translate analytics into actionable business solutions.

info_outline XNote: By applying to this position you will have an opportunity to share your preferred working location from the following: Mountain View, CA, USA; New York, NY, USA. Minimum qualifications: PhD in a quantitative discipline (e.g., Statistics, Biostatistics, Computer Science, Applied Mathematics, Operations Research, Economics) or another discipline involving experimental design and quantitative analysis of data. 1 year of experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or a relevant PhD degree. Experience in one or more of the following areas: coding (e.g., C/C++, Python, Java), databases and querying (e.g., SQL, MySQL, MapReduce, Hadoop), statistical analysis (e.g., R, Stata, SPSS, SAS), or hypothesis testing. Preferred qualifications: Experience with causal inference methods (e.g., split-testing, instrumental variables, difference-in-difference methods, fixed effects regression, panel data models, regression discontinuity, matching estimators). Experience with statistical programming languages, controlled experimentation, causal inference, and statistical data analysis (e.g., linear models, multivariate analysis, stochastic models, sampling methods, etc.). Applied experience with machine learning on large datasets. Ability to start full-time role in 2026. About the job Google is and always will be an engineering company. We hire people with a broad set of technical skills who are ready to take on some of technology's greatest challenges and make an impact on millions, if not billions, of users. At Google, data scientists not only revolutionize search, they routinely work on massive scalability, storage solutions, large-scale applications, and entirely new platforms for developers around the world. From Google Ads to Chrome, Android to YouTube, social to local, Google engineers are changing the world one technological achievement after another. As a Data Scientist, you will evaluate and improve Google's products. You will collaborate with a multi-disciplinary team of engineers and analysts on a wide range of problems. This position will bring scientific and statistical methods to the challenges of product creation, development, and improvement with an appreciation for the behaviors of the end user. 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. The US base salary range for this full-time position is $141,000-$202,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process. Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google. Responsibilities Collaborate with stakeholders in cross-projects and team settings to identify and clarify business or product questions to answer. Provide feedback to translate and refine business questions into tractable analysis, evaluation metrics, or mathematical models. Use custom data infrastructure or existing data models as appropriate, using specialized knowledge. Design and evaluate models to mathematically express and solve defined problems with limited precedent. Gather information, business goals, priorities, and organizational context around the questions to answer, as well as the existing and upcoming data infrastructure. Own the process of gathering, extracting, and compiling data across sources via relevant tools (e.g., SQL, R, Python). Format, restructure, or validate data to ensure quality and review the dataset to ensure it is ready for analysis.

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 work experience and a Master's degree). 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). About the job Help 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. AMeasurement is a cornerstone of performance advertising, driving the majority of Google Ads business growth. Accurate and unbiased measurement empowers bidding engines to maximize advertiser ROI, fostering growth for both advertisers and Google. The Product Analyst team applies advanced analytics to guide Google Ads strategy in this crucial area, ensuring that our advertising solutions effectively connect businesses with customers and deliver measurable results across our ad platforms. The AIM 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. As the Staff Product Data Scientist for Enterprise Platforms, you will help drive the vision of how large advertisers buy Google and third party advertising inventory efficiently. You will be responsible for setting the team's strategic direction, managing stakeholder relationships. 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. The US base salary range for this full-time position is $183,000-$271,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process. Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google. Responsibilities Perform analysis utilizing relevant tools (e.g., SQL, R, Python). Provide analytical thought leadership through proactive and strategic contributions (e.g., suggests new analyses, infrastructure or experiments to drive improvements in the business). Own outcomes for projects by covering problem definition, metrics development, data extraction and manipulation, visualization, creation, implementation of analytical/statistical models, and presentation to stakeholders. Develop solutions, lead, and manage problems that may be ambiguous and lacking clear precedent by framing problems, generating hypotheses, and making recommendations from a perspective that combines both, analytical and product-specific expertise. Oversee the integration of cross-functional and cross-organizational project/process timelines, develop process improvements and recommendations, and help define operational goals and objectives. Directly or indirectly oversee the contributions of others and develop colleagues' capabilities in the area of specialization.

Minimum qualifications: Master's degree in Statistics, Data Science, Mathematics, Physics, Economics, Operations Research, Engineering, or a related quantitative field. 3 years of work experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or a PhD degree. Preferred qualifications: 5 years of work experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or a PhD degree. Experience working with Large Language Models (LLM's) or applied AI. About the job Ads Metrics is the Data Scientist team for Search, Owned and Operated (O&O) ads. We support the Search Ads and Google Experience (SAGE) organisation in developing the most important ad products at Google. These products are at the heart of Google's business driving in annual growth and are advanced, and rapidly growing and evolving. We are also working on the most exciting projects related to AI (LLM Eval, AI Mode). 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. The US base salary range for this full-time position is $141,000-$202,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process. Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google. Responsibilities Collaborate with stakeholders in cross-projects and team settings to identify and clarify business or product questions to answer. Provide feedback to translate and refine business questions into tractable analysis, evaluation metrics, or mathematical models. Use custom data infrastructure or existing data models as appropriate, using specialized knowledge. Design and evaluate models to mathematically express and solve defined problems with limited precedent. Gather information, business goals, priorities, and organizational context around the questions to answer, as well as the existing and upcoming data infrastructure. Own the process of gathering, extracting, and compiling data across sources via relevant tools (e.g., SQL, R, Python). Format, re-structure, or validate data to ensure quality, and review the dataset to ensure it is ready for analysis.

_corporate_fare_ Google _place_ Mountain View, CA, USA **Advanced** Experience owning outcomes and decision making, solving ambiguous problems and influencing stakeholders; deep expertise in domain. **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. + Experience building predictive or causal models to understand user behaviors (such as churn, loyalty, engagement, etc.). **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). **About the job** Google Pixel phones, watches, and earbuds showcase the best of Google's hardware and AI. We develop technologies to make user experiences faster, more powerful, and seamless including industry leading camera features powered by Google's expertise in Artificial Intelligence and Machine Learning. The Pixel Data Science team's mission is to power the growth and evolution of the Pixel ecosystem. We bridge data, analytics, and business strategy, acting as essential thought partners to product and strategy leaders within the centralized Devices and Services Strategy and Operations (StratOps) organization. By uncovering critical insights and developing data-driven solutions, we optimize performance, enhance user experiences, and help scale the Google Pixel business. In this role, you will provide business critical insights, leveraging data to influence the direction of products. Your work will directly contribute to key decisions and the overall success of the Pixel line.The US base salary range for this full-time position is $183,000-$271,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process. Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more aboutbenefits at Google (************************************* . **Responsibilities** + Perform analysis on key Pixel metrics utilizing advanced investigative tools (e.g., SQL, R, Python). Own and execute the full workstream for Pixel dashboards, including data engineering, dashboard design, metrics definition, and insights sharing. + Own outcomes for projects by covering problem definition, metrics development, data extraction and manipulation, visualization, creation, and implementation of statistical models, and presentation to stakeholders. + Develop solutions for ambiguous problems lacking clear precedent by framing hypotheses and providing recommendations that combine investigative and product-specific expertise. + Liaise and align cross-functionally with Product Management, Marketing, Sales, and Executive leadership to translate analytics into actionable business solutions. Information collected and processed as part of your Google Careers profile, and any job applications you choose to submit is subject to Google'sApplicant and Candidate Privacy Policy (./privacy-policy) . Google is proud to be an equal opportunity and affirmative action employer. We are committed to building a workforce that is representative of the users we serve, creating a culture of belonging, and providing an equal employment opportunity regardless of race, creed, color, religion, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition (including breastfeeding), expecting or parents-to-be, criminal histories consistent with legal requirements, or any other basis protected by law. See also Google's EEO Policy (******************************************************* ,Know your rights: workplace discrimination is illegal (**************************************************************************** ,Belonging at Google (******************************** , and How we hire (**************************************** . If you have a need that requires accommodation, please let us know by completing our Accommodations for Applicants form (*************************************** . Google is a global company and, in order to facilitate efficient collaboration and communication globally, English proficiency is a requirement for all roles unless stated otherwise in the job posting. To all recruitment agencies: Google does not accept agency resumes. Please do not forward resumes to our jobs alias, Google employees, or any other organization location. Google is not responsible for any fees related to unsolicited resumes. 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 ******************************* and ************************************************************* If you have a 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. 3 years of work experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or a PhD degree. Experience with statistical and data analysis software (e.g., R, Python, MATLAB, pandas) and database languages (e.g., SQL). Preferred qualifications: PhD degree in Data Science, Operations Research, Industrial Engineering, Statistics, or related field. 4 years of relevant work experience (e.g., as a data scientist), including experience applying advanced analytics to planning and infrastructure problems. Experience designing and building supply chain models. Experience designing and building time-series forecasting, optimization, simulation, cost-tradeoff and probabilistic decision-making models. Knowledge of technical infrastructure for cloud computing. Excellent problem-framing, problem-solving, project management and team collaboration skills. About the job Operations Data Science is a team of Data Science (Analyst and Research) experts, who provide model-based decision support to scale Google's Technical Infrastructure optimally. In this role, you will help Google deliver Artificial Intelligence (AI) and Infrastructure at unparalleled scale, efficiency, reliability and velocity by contributing to the development of critical forecasting and capacity planning tools for Google's technical infrastructure. You will apply investigative methods (forecasting, optimization, simulation, probabilistic cost-tradeoffs and decision-making, operations research) to solve issues for Google's internal services, Google Cloud Platform, and Google's hardware supply chain. You will plan the machine-learning, compute, storage machines that train and serve all of Google and its customers, as part of a team whose mission is to: “Drive optimal capacity planning for machines and cluster networking by providing forecasts, models, policies, metrics and insights.” You will think critically about Google's cloud and AI as a technology, a business, and as an operation. You will be comfortable discussing total cost of ownership with hardware engineers, resource optimization with software engineers, and reviewing fleet plans and deployment policies with operations executives, all based upon the investigative models that you will be developing. Behind everything users see online is architecture built by AI and Infrastructure teams to keep it running. From developing and maintaining our data centers to building the next generation of Google platforms, we make Google's product portfolio possible. The US base salary range for this full-time position is $141,000-$202,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process. Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google. Responsibilities Collaborate with cross-functional stakeholder to understand their business needs and frame investigative problems. Develop, maintain, support, and enhance custom forecasting and capacity planning tools for Google's machine and network infrastructure. Drive direct analysis and modeling, drawing from multiple investigative methods and choose the right method and level of complexity appropriate for the business issues. Engage broadly to identify, prioritize, frame, and structure ambiguous issues, where data science projects or tools can have the biggest impact. Articulate business questions and use mathematical techniques to arrive at an answer using data. Translate analysis results into actionable business recommendations supported by technical documentation and presentations. Measure business outcomes driven from the investigative recommendations. Identify and communicate the issues, opportunities, and automation that the group should be working on.

info_outline XApplicants in San Francisco: Qualified applications with arrest or conviction records will be considered for employment in accordance with the San Francisco Fair Chance Ordinance for Employers and the California Fair Chance Act.Note: By applying to this position you will have an opportunity to share your preferred working location from the following: Sunnyvale, CA, USA; San Francisco, CA, USA. Minimum qualifications: Master's degree in a quantitative discipline such as Statistics, Engineering, Sciences, or equivalent practical experience. 4 years of experience in a data science role using data to influence business or product decisions. Experience analyzing data from various sources such as product instrumentation, customer support systems, and internal operational tools. Experience with SQL, Python or R programming including advanced data analysis, statistical modeling, and data visualization. Preferred qualifications: PhD degree in a relevant quantitative field. Experience in causal inference techniques to measure the true impact of business actions. Experience in Customer Support or Support-adjacent roles. Ability to work cross-functionally and communicate technical findings to non-technical audiences. Excellent product intuition and business acumen, with experience influencing both product and business strategy. About the job In this role, you will be using data to solve problems and you will be a key partner to stakeholders across product, operations, and engineering, helping to drive our strategy by analyzing the entire customer journey. You will address a wide range of issues, from optimizing product features and user behavior to analyzing the customer support experience and streamlining internal processes. You will use your investigative and statistical skills to make data-informed decisions across the board.The US base salary range for this full-time position is $166,000-$244,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process. Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google. Responsibilities Partner with product, operations, and engineering stakeholders to prioritize opportunities for improvement; collaborate with partner teams to define data requirements and build foundational datasets for key business and product initiatives. Drive and separately scope and analysis projects from inception to completion, defining success metrics and managing stakeholder communication along the way; design, execute, and analyze A/B experiments on product features, internal tools, and operational workflows to measure their impact. Apply causal inference and advanced statistical modeling to measure the impact of critical product and business initiatives and understand their key drivers. Manage analyses of the user journey to identify friction points and opportunities; translate investigative findings into actionable insights and narratives for various stakeholders. Perform opportunity sizing for new product and business initiatives to inform the roadmap and resource allocation.

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 work experience and a Master's degree). 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). About the job Help 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. We're looking for a creative data scientist to join a small, agile team developing new AI products and infrastructure. As part of this team, you will leverage your expertise to drive decision-making with data including making recommendations, measuring return on investment, and identifying new opportunities to pursue.Applied AI builds conversational agents deployed at a large scale that achieve very meaningful results in the real world. Some examples include the customer agent built for large call center environments, to fast food ordering handled by our Food AI agent. The team is transforming how enterprises connect with customers through the power of AI. We also offer unique experiences for team members where you get to work directly with the model builders (Google DeepMind / Vertex), learn and work with brilliant AI leaders, and have access to Global 1000 customers via our existing Google Cloud relationships. The opportunity in this space is tremendous. The US base salary range for this full-time position is $183,000-$271,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process. Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google. Responsibilities Perform analysis utilizing relevant tools (e.g., SQL, R, Python). Provide analytical thought leadership through proactive and contributions (e.g., suggests new analyses, infrastructure or experiments to drive improvements in the business). Own outcomes for projects by covering problem definition, metrics development, data extraction and manipulation, visualization, creation, implementation of analytical/statistical models, and presentation to stakeholders. Develop solutions, lead, and manage problems that may be ambiguous and lacking clear precedent by framing problems, generating hypotheses, and making recommendations from a perspective that combines both, analytical and product-specific expertise. Oversee the integration of cross-functional and cross-organizational project/process timelines, develop process improvements and recommendations, and help define operational goals and objectives. Directly or indirectly oversee the contributions of others and develop colleagues' capabilities in the area of specialization.

info_outline XApplicants in San Francisco: Qualified applications with arrest or conviction records will be considered for employment in accordance with the San Francisco Fair Chance Ordinance for Employers and the California Fair Chance Act.Note: By applying to this position you will have an opportunity to share your preferred working location from the following: Sunnyvale, CA, USA; Austin, TX, USA; San Francisco, CA, USA. Minimum qualifications: Master's degree in a quantitative discipline such as Statistics, Engineering, Sciences, or equivalent practical experience. 3 years of experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or a relevant PhD degree. 3 years of experience in data science, with a focus on time series analysis and forecasting. Experience in causal inference, A/B testing, statistical modeling, or machine learning. Experience with a range of forecasting methods, from classical statistical models to machine learning approaches. Preferred qualifications: 4 years of experience deploying and maintaining forecasting models in a live production environment. Experience with recent advancements in forecasting, such as foundation models (TimesFM) or deep learning approaches. Experience in a demand planning, contact center, or operational workforce management role. Familiarity with cloud platforms (e.g., Google Cloud Platform) and their AI/ML services (e.g., BigQuery, Vertex AI). Ability to apply judgmental forecasting and incorporate qualitative business adjustments into model outputs, especially for new or unprecedented events. About the job In this role, you will be responsible for developing and maintaining the models that predict our customer support case volume. Your work will be a critical input for the organization's staffing, budgeting, and planning, directly impacting our ability to deliver exceptional customer support at scale.The US base salary range for this full-time position is $141,000-$202,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process. Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google. Responsibilities Develop, deploy, and maintain time series forecasting models to predict customer support case volumes across various products, regions, and channels. Build and automate scalable data pipelines to ensure timely and reliable data for model training and inference. Monitor and evaluate model performance, dealing with key accuracy metrics, identifying model drift, and ensuring forecast reliability. Research and implement forecasting techniques to continuously improve model accuracy and capabilities. Partner with Operations, Finance, and leadership stakeholders to understand their planning needs, deliver forecasts, and explain variance drivers. Communicate forecast results and uncertainty to both technical and non-technical audiences to guide strategic decision-making.

info_outline XApplicants in San Francisco: Qualified applications with arrest or conviction records will be considered for employment in accordance with the San Francisco Fair Chance Ordinance for Employers and the California Fair Chance Act.Note: By applying to this position you will have an opportunity to share your preferred working location from the following: Sunnyvale, CA, USA; Austin, TX, USA; San Francisco, CA, USA. Minimum qualifications: Master's degree in a quantitative discipline such as Statistics, Engineering, Sciences, or equivalent practical experience. 3 years of experience in a data science role, with machine learning and Natural Language Processing (NLP) for developing and deploying AI/ML solutions. Experience with AI/ML libraries (e.g., TensorFlow, PyTorch, scikit-learn, Hugging Face). Preferred qualifications: PhD degree in Computer Science, Artificial Intelligence, Machine Learning, or a related quantitative field. Experience with Large Language Models (LLMs), including application in solving business problems. Experience in intelligent self-sustaining agents, including design, development, evaluation, and deployment. Experience with cloud platforms (e.g., Google Cloud Platform) and AI/ML services related to LLMs and generative AI. Experience in customer support or support-adjacent roles. Excellent programming skills in Python or a similar language with the ability to translate data into actionable insights and communicate findings to technical and non-technical stakeholders. About the job As a Business Data Scientist, you will be instrumental in driving customer success at scale by building the predictive, personalized, and proactive solutions that define the future of customer support. You will work with datasets to develop and deploy innovative AI/ML solutions, translating data into actionable strategies. The US base salary range for this full-time position is $141,000-$202,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process. Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google. Responsibilities Drive customer success at scale while researching and integrating advancements in Large Language Models (LLMs), Generative AI, and AI agent architectures to continuously enhance our capabilities and foster innovation. Lead development and deployment of advanced AI/ML solutions, with an emphasis on LLMs and intelligent self-sustaining, agents, addressing business issues. Implement evaluation frameworks and metrics for LLMs and AI agents, encompassing both traditional model performance and agent-specific evaluation criteria (e.g., task completion rate, reasoning quality). Monitor and maintain deployed LLM and AI agent solutions in production, including tracking key performance indicators, identifying and addressing model drift, and ensuring system stability and scalability. Identify and define AI/ML opportunities by collaborating with stakeholders to translate business needs into technical requirements and measurable outcomes.

_corporate_fare_ Google _place_ Sunnyvale, CA, USA; Austin, TX, USA; +2 more; +1 more **Mid** Experience driving progress, solving problems, and mentoring more junior team members; deeper expertise and applied knowledge within relevant area. _info_outline_ XApplicants in San Francisco: Qualified applications with arrest or conviction records will be considered for employment in accordance with the San Francisco Fair Chance Ordinance for Employers and the California Fair Chance Act.Note: By applying to this position you will have an opportunity to share your preferred working location from the following: **Sunnyvale, CA, USA; Austin, TX, USA; San Francisco, CA, USA** . **Minimum qualifications:** + Master's degree in a quantitative discipline such as Statistics, Engineering, Sciences, or equivalent practical experience. + 3 years of experience in a data science role, with machine learning and Natural Language Processing (NLP) for developing and deploying AI/ML solutions. + Experience with AI/ML libraries (e.g., TensorFlow, PyTorch, scikit-learn, Hugging Face). **Preferred qualifications:** + PhD degree in Computer Science, Artificial Intelligence, Machine Learning, or a related quantitative field. + Experience with Large Language Models (LLMs), including application in solving business problems. + Experience in intelligent self-sustaining agents, including design, development, evaluation, and deployment. + Experience with cloud platforms (e.g., Google Cloud Platform) and AI/ML services related to LLMs and generative AI. + Experience in customer support or support-adjacent roles. + Excellent programming skills in Python or a similar language with the ability to translate data into actionable insights and communicate findings to technical and non-technical stakeholders. **About the job** As a Business Data Scientist, you will be instrumental in driving customer success at scale by building the predictive, personalized, and proactive solutions that define the future of customer support. You will work with datasets to develop and deploy innovative AI/ML solutions, translating data into actionable strategies. The US base salary range for this full-time position is $141,000-$202,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process. Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more aboutbenefits at Google (************************************* . **Responsibilities** + Drive customer success at scale while researching and integrating advancements in Large Language Models (LLMs), Generative AI, and AI agent architectures to continuously enhance our capabilities and foster innovation. + Lead development and deployment of advanced AI/ML solutions, with an emphasis on LLMs and intelligent self-sustaining, agents, addressing business issues. + Implement evaluation frameworks and metrics for LLMs and AI agents, encompassing both traditional model performance and agent-specific evaluation criteria (e.g., task completion rate, reasoning quality). + Monitor and maintain deployed LLM and AI agent solutions in production, including tracking key performance indicators, identifying and addressing model drift, and ensuring system stability and scalability. + Identify and define AI/ML opportunities by collaborating with stakeholders to translate business needs into technical requirements and measurable outcomes. Information collected and processed as part of your Google Careers profile, and any job applications you choose to submit is subject to Google'sApplicant and Candidate Privacy Policy (./privacy-policy) . Google is proud to be an equal opportunity and affirmative action employer. We are committed to building a workforce that is representative of the users we serve, creating a culture of belonging, and providing an equal employment opportunity regardless of race, creed, color, religion, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition (including breastfeeding), expecting or parents-to-be, criminal histories consistent with legal requirements, or any other basis protected by law. See also Google's EEO Policy (******************************************************* ,Know your rights: workplace discrimination is illegal (**************************************************************************** ,Belonging at Google (******************************** , and How we hire (**************************************** . If you have a need that requires accommodation, please let us know by completing our Accommodations for Applicants form (*************************************** . Google is a global company and, in order to facilitate efficient collaboration and communication globally, English proficiency is a requirement for all roles unless stated otherwise in the job posting. To all recruitment agencies: Google does not accept agency resumes. Please do not forward resumes to our jobs alias, Google employees, or any other organization location. Google is not responsible for any fees related to unsolicited resumes. 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 ******************************* and ************************************************************* If you have a need that requires accommodation, please let us know by completing our Accommodations for Applicants form: ***************************************

_corporate_fare_ Google _place_ Sunnyvale, CA, USA **Mid** Experience driving progress, solving problems, and mentoring more junior team members; deeper expertise and applied knowledge within relevant area. **Minimum qualifications:** + Master's degree in Statistics, Data Science, Mathematics, Physics, Economics, Operations Research, Engineering, or a related quantitative field. + 3 years of work experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or a PhD degree. + Experience with statistical and data analysis software (e.g., R, Python, MATLAB, pandas) and database languages (e.g., SQL). **Preferred qualifications:** + PhD degree in Data Science, Operations Research, Industrial Engineering, Statistics, or related field. + 4 years of relevant work experience (e.g., as a data scientist), including experience applying advanced analytics to planning and infrastructure problems. + Experience designing and building supply chain models. + Experience designing and building time-series forecasting, optimization, simulation, cost-tradeoff and probabilistic decision-making models. + Knowledge of technical infrastructure for cloud computing. + Excellent problem-framing, problem-solving, project management and team collaboration skills. **About the job** Operations Data Science is a team of Data Science (Analyst and Research) experts, who provide model-based decision support to scale Google's Technical Infrastructure optimally. In this role, you will help Google deliver Artificial Intelligence (AI) and Infrastructure at unparalleled scale, efficiency, reliability and velocity by contributing to the development of critical forecasting and capacity planning tools for Google's technical infrastructure. You will apply investigative methods (forecasting, optimization, simulation, probabilistic cost-tradeoffs and decision-making, operations research) to solve issues for Google's internal services, Google Cloud Platform, and Google's hardware supply chain. You will plan the machine-learning, compute, storage machines that train and serve all of Google and its customers, as part of a team whose mission is to: "Drive optimal capacity planning for machines and cluster networking by providing forecasts, models, policies, metrics and insights." You will think critically about Google's cloud and AI as a technology, a business, and as an operation. You will be comfortable discussing total cost of ownership with hardware engineers, resource optimization with software engineers, and reviewing fleet plans and deployment policies with operations executives, all based upon the investigative models that you will be developing. Behind everything users see online is architecture built by AI and Infrastructure teams to keep it running. From developing and maintaining our data centers to building the next generation of Google platforms, we make Google's product portfolio possible. The US base salary range for this full-time position is $141,000-$202,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process. Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more aboutbenefits at Google (************************************* . **Responsibilities** + Collaborate with cross-functional stakeholder to understand their business needs and frame investigative problems. + Develop, maintain, support, and enhance custom forecasting and capacity planning tools for Google's machine and network infrastructure. + Drive direct analysis and modeling, drawing from multiple investigative methods and choose the right method and level of complexity appropriate for the business issues. + Engage broadly to identify, prioritize, frame, and structure ambiguous issues, where data science projects or tools can have the biggest impact. Articulate business questions and use mathematical techniques to arrive at an answer using data. + Translate analysis results into actionable business recommendations supported by technical documentation and presentations. Measure business outcomes driven from the investigative recommendations. Identify and communicate the issues, opportunities, and automation that the group should be working on. Information collected and processed as part of your Google Careers profile, and any job applications you choose to submit is subject to Google'sApplicant and Candidate Privacy Policy (./privacy-policy) . Google is proud to be an equal opportunity and affirmative action employer. We are committed to building a workforce that is representative of the users we serve, creating a culture of belonging, and providing an equal employment opportunity regardless of race, creed, color, religion, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition (including breastfeeding), expecting or parents-to-be, criminal histories consistent with legal requirements, or any other basis protected by law. See also Google's EEO Policy (******************************************************* ,Know your rights: workplace discrimination is illegal (**************************************************************************** ,Belonging at Google (******************************** , and How we hire (**************************************** . If you have a need that requires accommodation, please let us know by completing our Accommodations for Applicants form (*************************************** . Google is a global company and, in order to facilitate efficient collaboration and communication globally, English proficiency is a requirement for all roles unless stated otherwise in the job posting. To all recruitment agencies: Google does not accept agency resumes. Please do not forward resumes to our jobs alias, Google employees, or any other organization location. Google is not responsible for any fees related to unsolicited resumes. 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 ******************************* and ************************************************************* If you have a 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. 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. Preferred qualifications: 10 years of work experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or 8 years of work experience with a PhD degree. Experience with classifiers. About the job At YouTube, we believe that everyone deserves to have a voice, and that the world is a better place when we 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.The US base salary range for this full-time position is $197,000-$291,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process. Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google. Responsibilities Collaborate with stakeholders in cross-projects and team settings to identify and clarify business or product questions, providing feedback to translate and refine them into analysis, evaluation metrics, or mathematical models. Leverage custom data infrastructure or existing data models using specialized knowledge to design and evaluate models that mathematically express and solve defined problems. Gather information, business goals, priorities, and organizational context around the questions to answer, including the existing and upcoming data infrastructure. Own the process of gathering, extracting, and compiling data across sources via relevant tools (e.g., SQL, R, Python), formatting, re-structuring, or validating data to ensure quality, and readiness for analysis.