analytical data scientist

Data Scientist, Product Analytics

Amazon.com

<div><h2 class="jobSectionHeader">DESCRIPTION</h2><div>
The Sponsored Products and Brands team at Amazon Ads is re-imagining the advertising landscape through industry leading generative AI technologies, revolutionizing how millions of customers discover products and engage with brands across Amazon.com and beyond. We are at the forefront of re-inventing advertising experiences, bridging human creativity with artificial intelligence to transform every aspect of the advertising lifecycle from ad creation and optimization to performance analysis and customer insights. We are a passionate group of innovators dedicated to developing responsible and intelligent AI technologies that balance the needs of advertisers, enhance the shopping experience, and strengthen the marketplace. If you're energized by solving complex challenges and pushing the boundaries of what's possible with AI, join us in shaping the future of advertising. 
 
We are seeking an experienced Data Scientist to join the Sponsored Products Auction team. This team is responsible for building and evaluating mechanisms to rank and price billions of ad impressions per day. We're looking for a Data Scientist to define measures of auction efficiency and produce insights into the quality of inputs to our auction (supply, demand, ML model predictions). This role will also be responsible for exploratory data analysis to identify opportunities for improvement of the system and working closely with Economists, Applied Scientists and Engineers to improve our product. 
 
As a Data Scientist on this team, you will: 
<ul><li>Solve real-world problems by getting and analyzing large amounts of data, diving deep to identify business insights and opportunities, design simulations and experiments, developing statistical and ML models by tailoring to business needs, and collaborating with Scientists, Engineers, BIE's, and Product Managers.</li><li>Write code (Python, R, Scala, SQL, etc.) to obtain, manipulate, and analyze data
</li><li>Apply statistical and machine learning knowledge to specific business problems and data.</li><li>Build decision-making models and propose solution for the business problem you define.</li><li>Retrieve, synthesize, and present critical data in a format that is immediately useful to answering specific questions or improving system performance.</li><li>Analyze historical data to identify trends and support optimal decision making.</li><li>Formalize assumptions about how our systems are expected to work, create statistical definition of the outlier, and develop methods to systematically identify outliers. Work out why such examples are outliers and define if any actions needed.</li><li>Given anecdotes about anomalies or generate automatic scripts to define anomalies, deep dive to explain why they happen, and identify fixes.</li><li>Conduct written and verbal presentations to share insights to audiences of varying levels of technical sophistication.</li></ul> 
Why you will love this opportunity: Amazon is investing heavily in building a world-class advertising business. This team defines and delivers a collection of advertising products that drive discovery and sales. Our solutions generate billions in revenue and drive long-term growth for Amazon&rsquo;s Retail and Marketplace businesses. We deliver billions of ad impressions, millions of clicks daily, and break fresh ground to create world-class products. We are a highly motivated, collaborative, and fun-loving team with an entrepreneurial spirit - with a broad mandate to experiment and innovate. 
 
Impact and Career Growth: You will invent new experiences and influence customer-facing shopping experiences to help suppliers grow their retail business and the auction dynamics that leverage native advertising; this is your opportunity to work within the fastest-growing businesses across all of Amazon! Define a long-term science vision for our advertising business, driven from our customers' needs, translating that direction into specific plans for research and applied scientists, as well as engineering and product teams. This role combines science leadership, organizational ability, technical strength, product focus, and business understanding. 
 
Team video https://youtu.be/zD_6Lzw8raE</div><h2 class="jobSectionHeader">
BASIC QUALIFICATIONS</h2><ul><li>3+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience</li><li>2+ years of data scientist experience</li><li>3+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience</li><li>Bachelor's degree</li><li>Experience applying theoretical models in an applied environment</li></ul><h2 class="jobSectionHeader">
PREFERRED QUALIFICATIONS</h2><ul><li>Experience in Python, Perl, or another scripting language</li><li>Experience in a ML or data scientist role with a large technology company</li></ul> 
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. 
 
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you&rsquo;re applying in isn&rsquo;t listed, please contact your Recruiting Partner. 
The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life &amp; AD&amp;D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits. 
USA, NY, New York - 153,400.00 - 207,500.00 USD annually 
USA, WA, SEATTLE - 136,000.00 - 184,000.00 USD annually</div>

Data Scientist

TripleLift

<div><div>About TripleLift

We're TripleLift, an advertising platform on a mission to elevate digital advertising through beautiful creative, quality publishers, actionable data and smart targeting. Through over 1 trillion monthly ad transactions, we help publishers and platforms monetize their businesses. Our technology is where the world's leading brands find audiences across online video, connected television, display and native ads. Brand and enterprise customers choose us because of our innovative solutions, premium formats, and supportive experts dedicated to maximizing their performance.
As part of the Vista Equity Partners portfolio, we are NMSDC certified, qualify for diverse spending goals and are committed to economic inclusion. Find out how TripleLift raises up the programmatic ecosystem at triplelift.com.</div>
TripleLift, a fast-growing startup tackling some of the most challenging problems in the world of digital advertising, is seeking a Data Scientist with a focus on optimization strategies for our real-time ad marketplace. As a Data Scientist at TripleLift, you will contribute to experiments to understand bidding behaviors in our real-time marketplace, improving the performance of traffic shaping algorithms, and optimizing outcomes for Publishers, DSPs and TripleLift alike. You will build proof of concept models, put ML models in production, create reusable features and data structures, and collaborate with cross-functional teams to drive Data Science initiatives forward.

Responsibilities
<ul>
<li>Conduct research and experiments to improve the performance of our traffic shaping algorithms and maximize performance for our customers</li>
<li>Build new traffic shaping optimization strategies based on cutting edge research, build proof of concept ML models, and drive them to successful outcomes in full scale production</li>
<li>Support analytics projects in partnership with Product, Engineering, and cross-functional teams to support and influence product strategies</li>
<li>Monitor and measure statistical modeling performance, and build dashboards and alerts to ensure models are functioning effectively</li>
<li>Build reusable modules and data structures, and provide guidance and feedback to team members on their work, taking into account their skills, backgrounds and working styles</li>
<li>Take ownership of complex technical challenges, demonstrating initiative in navigating ambiguity and championing engineering best practices and innovation.</li>
</ul>
Qualifications
<ul>
<li>Bachelor's degree or higher in a related quantitative field (E.g. Mathematics, Computer Science, Engineering)</li>
<li>2+ years of work experience in Data Science / Machine Learning</li>
<li>Familiarity with tools used in our tech stack is a plus (e.g. Python, Spark, AWS, Docker, DataBricks, ONNX, MySQL, Snowflake and Airflow)</li>
<li>Familiarity with ML libraries like scikit-learn to quickly analyze data and prototype models that can be used in high volume distributed systems</li>
<li>Familiarity with monitoring and measuring statistical modeling performance via dashboards and alerts, using tools like Prometheus, Grafana, Looker, etc., to make sure models are functioning effectively</li>
<li>Solid software engineering fundamentals, including version control, testing, and writing clean, maintainable, and production-ready code</li>
<li>Excellent technical communication skills</li>
<li>Strong analytical and problem-solving skills</li>
<li>Committed to a process of continuous learning and spreading subject matter expertise</li>
</ul>
Technologies

From our early days, we've always believed in using the right tools for the right job and continue to explore new technology options as we grow. The Data Science team uses the following technologies at TripleLift:
<ul>
<li>Languages: Python, Java</li>
<li>Frameworks: Spark, DataBricks, ONNX, Docker, Airflow</li>
<li>Databases: MySQL, Snowflake, S3/Parquet</li>
<li>Amazon Web Services to keep everything running</li>
</ul><div>
Life at TripleLift

At TripleLift, we're a team of great people who like who they work with and want to make everyone around them better. This means being positive, collaborative, and compassionate. We hustle harder than the competition and are continuously innovating.
Learn more about TripleLift and our culture by visiting our LinkedIn Life page.

Establishing People, Culture and Community Initiatives

At TripleLift, we are committed to building a culture where people feel connected, supported, and empowered to do their best work. We invest in our people and foster a workplace that encourages curiosity, celebrates shared values, and promotes meaningful connections across teams and communities. We want to ensure the best talent of every background, viewpoint, and experience has an opportunity to be hired, belong, and develop at TripleLift. Through our People, Culture, and Community initiatives, we aim to create an environment where everyone can thrive and feel a true sense of belonging.

Privacy Policy

Please see our Privacy Policies on our TripleLift and 1plusX websites.

TripleLift does not accept unsolicited resumes from any type of recruitment search firm. Any resume submitted in the absence of a signed agreement will become the property of TripleLift and no fee shall be due.</div></div>

DataAnnotation

<div>
 We are looking for a Data Scientist to join our team to train AI models. You will measure the progress of these AI chatbots, evaluate their logic, and solve problems to improve the quality of each model.
 
 
 In this role you will need to hold an expert understanding of data analysis. Other related fields include, but are not limited to: Applied skills in Statistics and/or Computer Science.
 
 
 
 Benefits
 
 
 
 <ul>
 <li>
 This is a full-time or part-time REMOTE position
 </li>
 <li>
 You&rsquo;ll be able to choose which projects you want to work on
 </li>
 <li>
 You can work on your own schedule
 </li>
 <li>
 Projects are paid hourly starting at $40+ USD per hour, with bonuses on high-quality and high-volume work
 
 
 </li>
 </ul>
 
 Responsibilities
 
 
 
 <ul>
 <li>
 Give AI chatbots writing and editing tasks and evaluate their outputs
 </li>
 <li>
 Evaluate the quality produced by AI models for correctness and performance
 
 
 </li>
 </ul>
 
 Qualifications
 
 
 
 <ul>
 <li>
 Fluency in English (native or bilingual level)
 </li>
 <li>
 Detail-oriented
 </li>
 <li>
 Demonstrated proficiency in related technical, statistical, and mathematical skills
 </li>
 <li>
 A current, in progress, or completed Masters and/or PhD is preferred but not required
 
 
 </li>
 </ul>
 
 Notes
 
 
 
 Payment is made via PayPal. We will never ask for any money from you. PayPal will handle any currency conversions from USD. Only applicants in the United States will be considered for this role. This is an independent contract position.
 
 
 #math
</div>

<div>
 As a Data Engineer at Meta, you will shape the future of people-facing and business-facing products we build across our entire family of applications (Facebook, Instagram, Messenger, WhatsApp, Reality Labs, Threads). Your technical skills and analytical mindset will be utilized designing and building some of the world's most extensive data sets, helping to craft experiences for billions of people and hundreds of millions of businesses worldwide.In this role, you will collaborate with software engineering, data science, and product management teams to design/build scalable data solutions across Meta to optimize growth, strategy, and user experience for our 3 billion plus users, as well as our internal employee community.You will be at the forefront of identifying and solving some of the most interesting data challenges at a scale few companies can match. By joining Meta, you will become part of a world-class data engineering community dedicated to skill development and career growth in data engineering and beyond.Data Engineering: You will guide teams by building optimal data artifacts (including datasets and visualizations) to address key questions. You will refine our systems, design logging solutions, and create scalable data models. Ensuring data security and quality, and with a strong focus on efficiency, you will suggest architecture and development approaches and data management standards to address complex analytical problems.Product leadership: You will use data to shape product development, identify new opportunities, and tackle upcoming challenges. You'll ensure our products add value for users and businesses, by prioritizing projects, and driving innovative solutions to respond to challenges or opportunities.Communication and influence: You won't simply present data, but tell data-driven stories. You will convince and influence your partners using clear insights and recommendations. You will build credibility through structure and clarity, and be a trusted strategic partner.
 
 
 Data Engineer, Product Analytics Responsibilities:
 
 
 <ul>
 <li>
 Conceptualize and own the data architecture for multiple large-scale projects, while evaluating design and operational cost-benefit tradeoffs within systems
 </li>
 <li>
 Create and contribute to frameworks that improve the efficacy of logging data, while working with data infrastructure to triage issues and resolve
 </li>
 <li>
 Collaborate with engineers, product managers, and data scientists to understand data needs, representing key data insights in a meaningful way
 </li>
 <li>
 Define and manage Service Level Agreements for all data sets in allocated areas of ownership
 </li>
 <li>
 Determine and implement the security model based on privacy requirements, confirm safeguards are followed, address data quality issues, and evolve governance processes within allocated areas of ownership
 </li>
 <li>
 Design, build, and launch collections of sophisticated data models and visualizations that support multiple use cases across different products or domains
 </li>
 <li>
 Solve our most challenging data integration problems, utilizing optimal Extract, Transform, Load (ETL) patterns, frameworks, query techniques, sourcing from structured and unstructured data sources
 </li>
 <li>
 Assist in owning existing processes running in production, optimizing complex code through advanced algorithmic concepts
 </li>
 <li>
 Optimize pipelines, dashboards, frameworks, and systems to facilitate easier development of data artifacts
 </li>
 <li>
 Influence product and cross-functional teams to identify data opportunities to drive impact
 </li>
 <li>
 Mentor team members by giving/receiving actionable feedback
 
 
 </li>
 </ul>
 Minimum Qualifications:
 
 
 <ul>
 <li>
 Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
 </li>
 <li>
 4+ years of experience where the primary responsibility involves working with data. This could include roles such as data analyst, data scientist, data engineer, or similar positions
 </li>
 <li>
 4+ years of experience with SQL, ETL, data modeling, and at least one programming language (e.g., Python, C++, C#, Scala, etc.)
 
 
 </li>
 </ul>
 Preferred Qualifications:
 
 
 <ul>
 <li>
 Master's or Ph.D degree in a STEM field
 </li>
 <li>
 Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)
 </li>
 <li>
 Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)
 </li>
 <li>
 Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies
 
 
 </li>
 </ul>
 About Meta:
 
 
 Meta builds technologies that help people connect, find communities, and grow businesses. When Facebook launched in 2004, it changed the way people connect. Apps like Messenger, Instagram and WhatsApp further empowered billions around the world. Now, Meta is moving beyond 2D screens toward immersive experiences like augmented and virtual reality to help build the next evolution in social technology. People who choose to build their careers by building with us at Meta help shape a future that will take us beyond what digital connection makes possible today&mdash;beyond the constraints of screens, the limits of distance, and even the rules of physics.
 
 
 Meta is proud to be an Equal Employment Opportunity and Affirmative Action employer. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, transgender status, sexual stereotypes, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics. We also consider qualified applicants with criminal histories, consistent with applicable federal, state and local law. Meta participates in the E-Verify program in certain locations, as required by law. Please note that Meta may leverage artificial intelligence and machine learning technologies in connection with applications for employment.
 
 
 Meta is committed to providing reasonable accommodations for candidates with disabilities in our recruiting process. If you need any assistance or accommodations due to a disability, please let us know at accommodations-ext@meta.com.
 
 
 $147,000/year to $208,000/year + bonus + equity + benefits
 
 
 Individual compensation is determined by skills, qualifications, experience, and location. Compensation details listed in this posting reflect the base hourly rate, monthly rate, or annual salary only, and do not include bonus, equity or sales incentives, if applicable. In addition to base compensation, Meta offers benefits. Learn more about benefits at Meta.
</div>

Data Engineer, Product Analytics

Roku

<div>
 
 Teamwork makes the stream work.
 
 
 
 
 
 
 Roku is changing how the world watches TV
 
 
 
 Roku is the #1 TV streaming platform in the U.S., Canada, and Mexico, and we've set our sights on powering every television in the world. Roku pioneered streaming to the TV. Our mission is to be the TV streaming platform that connects the entire TV ecosystem. We connect consumers to the content they love, enable content publishers to build and monetize large audiences, and provide advertisers unique capabilities to engage consumers.
 
 
 From your first day at Roku, you'll make a valuable - and valued - contribution. We're a fast-growing public company where no one is a bystander. We offer you the opportunity to delight millions of TV streamers around the world while gaining meaningful experience across a variety of disciplines.
 
 
 
 
 
 
 
 
 
 About the team
 
 
 
 The Core Analytics Team is a centralized function dedicated to providing data-driven insights to drive business and product success. We work closely with our Product, Engineering, and Marketing teams to deliver exceptional experiences to our customers while maximizing the value proposition for the business.
 
 
 
 
 
 
 
 
 
 About the role
 
 
 
 Roku is looking for a Data Scientist to join the Core Analytics team and provide support for our Customer Intelligence function, part of the broader Planning &amp; Optimization team. Together, we answer high-impact business questions from senior leaders with clear, decision-ready insights. You&rsquo;ll work on customer analytics that directly shape how Roku grows engagement, retention and monetization across the streaming ecosystem, with visibility to cross-functional leaders and meaningful ownership over high-impact questions.
 
 
 
 
 
 This role is more than analytics and is intentionally &ldquo;business-forward&rdquo;. We're looking for someone who can translate customer behavior into metrics and narratives which can help define our customer strategy, and/or measure the impact of initiatives on customer behavior. You&rsquo;ll be expected to translate ambiguous stakeholder needs into strong analytical narratives and executive-ready deliverables. Familiarity with causal inference/experimentation is important; deep specialization is a plus but not required. This is a hybrid role with four days per week in the office, Monday through Thursday. The selected candidate will be based out of NYC.
 
 
 For New York Only - The estimated annual salary for this position is between $135,000-$153,000 annually.
 
 
 
 
 
 Compensation packages are based on factors unique to each candidate, including but not limited to skill set, certifications, and specific geographical location. This role is eligible for health insurance, equity awards, life insurance, disability benefits, parental leave, wellness benefits, and paid time off.
 
 
 
 
 
 
 
 
 
 What you'll be doing
 
 
 <ul>
 <li>
 Own end-to-end analyses: scope the question, define success metrics, pull data, analyze, synthesize, and deliver data-driven narratives.
 </li>
 <li>
 Drive stakeholder alignment: clarify objectives, assumptions, tradeoffs, and decision points; ensure outputs are usable.
 </li>
 <li>
 Build crisp storytelling &amp; presentations: create executive-ready readouts (slides, memos) with clear &ldquo;so what / now what.&rdquo;
 </li>
 <li>
 Develop SQL and Python-based workflows: write and review SQL/Python code to create datasets, compute KPIs, and validate results; use Airflow to maintain and build new pipelines when needed.
 </li>
 <li>
 Create reporting in Tableau/Looker: develop dashboards or recurring scorecards that make performance tracking easier and reduce ad-hoc churn.
 </li>
 <li>
 Measurement &amp; causal thinking: apply or partner on quasi-experimental approaches (e.g., diff-in-diff, propensity matching, synthetic controls) with appropriate caveats to address incrementality questions.
 </li>
 <li>
 Raise analytical quality: ensure statistical rigor, bias awareness, and clear limitations.
 </li>
 </ul>
 
 
 
 
 
 
 
 
 We're excited if you have
 
 
 <ul>
 <li>
 3+ years (or equivalent) in analytics/data science roles driving business decisions (tech, media, marketplaces, consumer products, etc.).
 </li>
 <li>
 Strong SQL (joins, window functions, building analysis-ready tables, QA/validation).
 </li>
 <li>
 Proficiency in Excel to work with data, tables and visualization.
 </li>
 <li>
 Strong ability to communicate insights: structured thinking, clear writing, confident presenting to non-technical and executive audiences.
 </li>
 <li>
 Solid foundation in statistics (hypothesis testing, confidence intervals, regression basics).
 </li>
 <li>
 Experienced with Python for analysis and data pipeline production (via Airflow).
 </li>
 <li>
 Hands-on experience with visualization tools like Tableau or Looker
 </li>
 </ul>
 
 
 
 
 
 
 
 
 Our Hybrid Work Approach
 
 
 
 Roku fosters an inclusive and collaborative environment where teams work in the office Monday through Thursday. Fridays are flexible for remote work except for employees whose roles are required to be in the office five days a week or employees who are in offices with a five day in office policy.
 
 
 
 
 
 
 
 
 
 Benefits
 
 
 
 Roku is committed to offering a diverse range of benefits as part of our compensation package to support our employees and their families. Our comprehensive benefits include global access to mental health and financial wellness support and resources. Local benefits include statutory and voluntary benefits which may include healthcare (medical, dental, and vision), life, accident, disability, commuter, and retirement options (401(k)/pension). Our employees can take time off work for vacation and other personal reasons to balance their evolving work and life needs. It's important to note that not every benefit is available in all locations or for every role. For details specific to your location, please consult with your recruiter.
 
 
 
 
 
 
 
 
 
 Accommodations
 
 
 
 Roku welcomes applicants of all backgrounds and provides reasonable accommodations and adjustments in accordance with applicable law. If you require reasonable accommodation at any point in the hiring process, please direct your inquiries to EmployeeRelations@Roku.com.
 
 
 
 
 
 
 
 
 
 The Roku Culture
 
 
 
 Roku is a great place for people who want to work in a fast-paced environment where everyone is focused on the company's success rather than their own. We try to surround ourselves with people who are great at their jobs, who are easy to work with, and who keep their egos in check. We appreciate a sense of humor. We believe a fewer number of very talented folks can do more for less cost than a larger number of less talented teams. We're independent thinkers with big ideas who act boldly, move fast and accomplish extraordinary things through collaboration and trust. In short, at Roku you'll be part of a company that's changing how the world watches TV.
 
 
 We have a unique culture that we are proud of. We think of ourselves primarily as problem-solvers, which itself is a two-part idea. We come up with the solution, but the solution isn't real until it is built and delivered to the customer. That penchant for action gives us a pragmatic approach to innovation, one that has served us well since 2002.
 
 
 To learn more about Roku, our global footprint, and how we've grown, visit https://www.weareroku.com/factsheet.
 
 
 
 
 
 By providing your information, you acknowledge that you want Roku to contact you about job roles, that you have read Roku's Applicant Privacy Notice, and understand that Roku will use your information as described in that notice. If you do not wish to receive any communications from Roku regarding this role or similar roles in the future, you may unsubscribe at any time by emailing WorkforcePrivacy@Roku.com.
 
</div>

Google

<div>Note: 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.<h3 class="jobSectionHeader">
Minimum qualifications:</h3><ul>
<li>Master's degree in Statistics, Data Science, Mathematics, Physics, Economics, Operations Research, Engineering, or a related quantitative field.</li>
<li>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.</li></ul> 
<h3 class="jobSectionHeader">
Preferred qualifications:</h3><ul>
<li>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.</li>
<li>Familiarity with modern Machine Learning and Large Language Model (LLM) techniques.</li>
<li>Ability to commit to knowledge and learning, respect for science, tolerance for ambiguity, and interest in practical application of science to business.</li>
<li>Excellent collaboration skills, with the ability to collaborate cross-functionally and work effectively with Data Scientist (DS), User Experience Researcher (UXR), product and engineering partners.</li>
</ul><div><h2 class="jobSectionHeader">About the job</h2>
In this role, you will partner cross-functionally to drive Google's mission of organizing the world&rsquo;s information and making it universally accessible and useful. As technology continues to evolve, your commitment remains to help users in their journey to connect to helpful information more easily, leveraging technology to find new ways to satisfy users' information needs. 
 
In this role, you will provide users with relevant and meaningful information based on their interests and understanding of the world&rsquo;s information. Your mission is to make it effortless for people to catch up on their interests by bringing together informative, entertaining content from the voices they care about. 
 
As a part of the Discover Data Science team, you will partner with cross-functional to drive that mission with a data-informed strategy, identifying opportunities and accelerating execution. As a part of the Discover Personalization and Quality team, you will partner with engineering and product, develop deep understanding of how to build a personalized retrieval and ranking system that delivers high-quality, compelling and valuable content. You will leverage a wide range of analysis tools (including metrics and AI raters, statistical modeling, cohort and exploratory analyses), and incorporate AI-driven understanding to define the job of a data scientist for the new era.The US base salary range for this full-time position is $207,000-$300,000 + 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.<div><div> 
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.</div></div></div><div><h2 class="jobSectionHeader">
Responsibilities</h2><ul>
<li>Lead core understanding of retrieval and ranking ML systems and collaborate with engineers to deliver significant improvements that accelerate product growth.</li>
<li>Analyze systems to identify opportunities while maintaining end-to-end ownership of research agenda, execution, and insight delivery to leadership.</li>
<li>Build expertise in retrieval and ranking systems, advocating for changes, where needed, and driving cross-functional alignment.</li>
<li>Contribute as an individual contributor, as well as a Technical Lead for a small group of data scientists.</li>
<li>Manage ambiguous data science problems, and leveraging new technology to produce quantum leaps forward in understanding, such as via LLM-driven tooling.</li>
</ul></div>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.</div>

Staff Data Scientist, Discover Personalization and Quality

Explore 856+ Analytical data scientist in New York this April. Find roles across top companies and apply now to boost your career.

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Staff Data Scientist, Discover Personalization and Quality