Lead Data Scientist - Recommendations

Scribd, Inc. is on a mission to advance human understanding. Our four products — Scribd®, Slideshare®, Everand™, and Fable — help billions of people across the globe move beyond access and into insight, application, and expertise.

We support a culture where our employees can be real and be bold; where we debate and commit as we embrace plot twists; and where every employee is empowered to take action as we prioritize the customer.

We believe the best work happens when individual flexibility is balanced with meaningful community connection. Scribd Flex empowers employees to choose the workstyle and location that support their best performance, while committing to intentional in-person moments that strengthen collaboration and culture. Occasional in-person attendance is required for all Scribd, Inc. employees, regardless of location.

So what are we looking for in new team members? At Scribd, Inc., we hire for “GRIT.” Traditionally defined as the intersection of passion and perseverance toward long-term goals, GRIT reflects the mindset we expect from every employee. For us, it also serves as a practical framework for how we work: setting and achieving Goals, delivering Results within your role, contributing Innovative ideas and solutions, and strengthening the broader Team through collaboration and attitude.

This posting reflects an approved, open position within the organization.

About the Role

Scribd, Inc.’s Data & Analytics team is hiring a Lead Data Scientist to own measurable outcomes across our recommendation surfaces – translating product goals into metrics, leading roadmap bets, and shipping lifts in business results. You’ll define the offline/online contract end-to-end, design and run experiments, diagnose why variants win or lose, and build prototype models while partnering with Engineering to productionize. You’ll map goals to metrics with clear success criteria, focus on opportunity sizing and measurement, and apply an AI lens (LLMs, embeddings) where it demonstrably improves retrieval, ranking, or understanding—shaping how millions engage with our global content library.

Scribd is a differentiated subscription platform with strong organic reach and a vast catalog—books, audiobooks, and hundreds of millions of UGC documents and slides. In a landscape reshaped by AI, our opportunity is to help users cut through noise and discover high-quality, human-centered content. You’ll set north stars and guardrails, create leading indicators that predict long-term outcomes, and build the measurement architecture—identity, attribution windows, metric contracts, and drift/leakage checks—that keeps downstream metrics trustworthy. You’ll also accelerate decision velocity with clear stop/go criteria and power checks, and tell the story through concise decision memos with trade-offs and risks.

What you’ll do:

• Opportunity mapping. Size and prioritize new recs surfaces, intents, and cohorts; trace the funnel and analyze by slice (cold items, long-tail users, platform) to steer the roadmap.

• Own the evaluation framework. Define north star & guardrails (e.g. diversity, novelty, duplication, safety); set threshold and tradeoffs, and publish the Objective & Eval Contract per surface.

• Offline/Online alignment. Quantify correlation between offline IR metrics (e.g., NDCG@K, MAP, MRR, coverage, calibration) and online KPIs by surface/cohort; publish error bounds and monitor metric drift.

• Create leading indicators. Create short-horizon metrics that predict long-term outcomes (e.g., trial to bill-through); backtest and run post-hoc causal checks, reporting uncertainty.

• Build the measurement architecture. Set identity & attribution standards (user_id vs. device_id, qualifying events, windows) so downstream metrics (bill-through, churn) are trustworthy.

• Design and run advanced experiments such as interleaving tests, pre-register stop/go criteria, and deliver crisp readouts that drive decisions.

• Codify schemas, freshness, leakage, and drift checks with Analytics and Data Engineers, establish high quality datasets for Recs algo.

• Evaluate when LLMs/embeddings (topics, summaries, semantic similarity) measurably improve offline/online metrics; prototype and hand off clear build specs to ML Eng.

• Storytelling and influence. Write decision memos, align cross-functional teams, and drive clear decisions with trade-offs and risks called out.

What you’ll need:

• 8+ years experience in Data Science, preferably on recs/search/ranking with shipped impact.

• Strong Python and SQL; comfort with Spark.

• Fluency in ranking evaluation (NDCG@K, MAP, MRR, calibration, coverage/diversity) and awareness of exposure/selection bias.

• Fluency in experiment design and connecting offline metrics to online outcomes.

• Ability to translate product goals into loss functions, features, and specs engineers can build.

Nice to have:

• Familiarity with LLMs/embeddings evaluation in offline and online; embeddings/vector search assessment for lift vs. latency/cost

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At Scribd, Inc., your base pay is one part of your total compensation package and is determined within a range. Our pay ranges are based on the local cost of labor benchmarks for each specific role, level, and geographic location. San Francisco is our highest geographic market in the United States.

In the state of California, the reasonably expected salary range is between $162,000 [minimum salary in our lowest geographic market within California] to $252,500 [maximum salary in our highest geographic market within California].

In the United States, outside of California, the reasonably expected salary range is between $133,000 [minimum salary in our lowest US geographic market outside of California] to $239,500 [maximum salary in our highest US geographic market outside of California].

In Canada, the reasonably expected salary range is between $169,000 CAD[minimum salary in our lowest geographic market] to $224,500 CAD[maximum salary in our highest geographic market].

We carefully consider a wide range of factors when determining compensation, including but not limited to experience; job-related skill sets; relevant education or training; and other business and organizational needs. The salary range listed is for the level at which this job has been scoped. In the event that you are considered for a different level, a higher or lower pay range would apply. This position is also eligible for a competitive equity ownership, and a comprehensive and generous benefits package.

Are you currently based in a location where Scribd, Inc. can employ you?
Employees must have their primary residence in or near one of the following cities. This includes surrounding metro areas or locations within a typical commuting distance:

United States:

Atlanta | Austin | Boston | Dallas | Denver | Chicago | Houston | Jacksonville | Los Angeles | Miami | New York City | Phoenix | Portland | Sacramento | Salt Lake City | San Diego | San Francisco | Seattle | Washington D.C.

Canada:

Ottawa | Toronto | Vancouver

Mexico:

Mexico City

Benefits at Scribd, Inc.

• Scribd Flex (flexible work model)

• Comprehensive health, dental, and vision coverage

• Mental health support and disability coverage

• Generous paid time off, including vacation, sick time, holidays, winter break, volunteer time, and sabbaticals

• Paid parental leave and family support benefits

• Retirement matching and employee equity

• Learning and development programs and professional growth opportunities

• Wellness and home office stipends

• Complimentary access to the Scribd, Inc. suite of products

• Enterprise access to leading AI tools

Get to Know Scribd, Inc.
About Scribd, Inc.
Life at Scribd, Inc.

We want our interview process to be accessible to everyone. You can inform us of any reasonable adjustments we can make to better accommodate your needs by emailing [email protected] about the need for adjustments at any point in the interview process.

Scribd, Inc. is committed to equal employment opportunity regardless of race, color, religion, national origin, gender, sexual orientation, age, marital status, veteran status, disability status, or any other characteristic protected by law. We encourage people of all backgrounds to apply, and believe that a diversity of perspectives and experiences create a foundation for the best ideas. Come join us in building something meaningful.