Senior Product & PLG Analyst (Full-Stack Data Scientist)

Nebius
New York, NY
On-siteCareer-pivot friendly

Who this role is best for

Best suited to candidates with strong statistical and technical expertise working in a SaaS or API-first company.

Best fit for

  • Candidates with 5+ years of SaaS product analytics experience and a track record of independent end-to-end projects
    — “5+ years of experience as a Product / Growth Analyst, Data Scientist or equivalent.”
  • Individuals who have built and deployed predictive models in production environments
    — “Hands-on experience building, validating and deploying predictive models that were used to make real business decisions.”

Things to consider

  • The position is expected to take full ownership of analytical pipelines and models without dependency on others
    — “This role is fully independent. When a question comes up, you take it all the way.”

How to stand out

  • Emphasize experience with large, messy datasets and your ability to derive actionable insights from them
    — “Comfort working with large, messy, event-level datasets.”
  • Showcase your ability to translate complex analysis into clear, actionable recommendations for leadership
    — “Strong communication: you can turn complex analysis into a clear, compelling story and a concrete recommendation.”
  • Demonstrate experience with data orchestration and SQL-based data modeling using dbt and Snowflake/BigQuery
    — “Experience with modern data tooling (Snowflake/BigQuery, dbt, Airflow, and BI tools like Omni/Looker/Tableau).”
  • Include examples of influencing business strategy through data and cross-functional collaboration
    — “Demonstrated ability to influence business strategy through data and drive alignment across cross-functional stakeholders.”
Pace · Fast PacedCollaboration · HighAutonomy · HighDecision Impact · Company

Derived from job-description analysis by Serendipath's career intelligence engine.

What success looks like

  • product success metrics
  • strategic product decisions
Typical background
product managementdata science

Skills & requirements

Required

Product And PLG AnalyticsSelf-serve Motion MetricsPredictive ModelsExperiments Design

Preferred

AI AgentsRetrieval Systems

Stack & domain

Product AnalyticsPLG AnalyticsSelf-serve MotionSignupActivationUsageConversionExpansionRetentionData PipelinesModelsSQLdbtPythonOrchestrationPredictive ModelsConversion PropensityChurn RiskUsage ForecastingLead ScoringAccount ScoringExperimentsA/B TestsPricing And Packaging TestsOnboarding ChangesCausal InferenceMetric DefinitionsShared Source Of TruthAnalytical RigorCommunicationProblem-solvingAdaptabilityTeamworkCollaborationStrategic ThinkingDecision-makingAICloud InfrastructureGlobal AI EconomyFull-stack AI Cloud PlatformData And Model TrainingProduction DeploymentAI AgentsRetrieval SystemsTrustworthy DataReal-time InformationAi/ml InfrastructureGPU OrchestrationInference OptimizationComputeStorageNetworkingApplied AIProduct SuccessGrowth LeversProduct BetsMarket Opportunities

About the role

Original posting from Nebius

About Nebius:

Nebius is leading a new era in cloud infrastructure for the global AI economy. We are building a full-stack AI cloud platform that supports developers and enterprises from data and model training through to production deployment, without the cost and complexity of building large in-house AI/ML infrastructure.

Built by engineers, for engineers. From large-scale GPU orchestration to inference optimization, we own the hard problems across compute, storage, networking and applied AI.

Listed on Nasdaq (NBIS) and headquartered in Amsterdam, we have a global footprint with R&D hubs across Europe, the UK, North America and Israel. Our team of 1,500+ includes hundreds of engineers with deep expertise across hardware, software and AI R&D.

About the Tavily at Nebius

In a rapidly evolving world, trust in AI depends on AI agents being grounded in fresh, verified real-world data. Search is the foundation that makes this possible.

Tavily provides the search and intelligence layer that powers AI agents and retrieval systems with trustworthy, real-time information. We work with some of the most innovative teams in AI, from fast-growing startups to global enterprises, helping them build agents that are not only intelligent but informed.

About the Role

We're looking for a senior, full-stack analyst / data scientist to own Product and PLG analytics end-to-end. You'll own the metrics behind our self-serve motion (signup, activation, usage, conversion, expansion and retention) and find the drivers behind them. You'll work directly with our CEO and leadership as a thought partner on product and growth decisions.

This role is fully independent. When a question comes up, you take it all the way: from building the pipeline, model the data, train and deploy the model, analyze the results and come back with a clear recommendation. Nothing waits in a queue for someone else. You'll also work closely with the other analysts on the team, share methods and standards, and collaborate across Product, Engineering, Growth, Marketing and GTM.

What You'll Do

  • Own Product and PLG analytics end-to-end: define, instrument and measure the self-serve funnel, from first API call through activation, conversion to paid, expansion and churn.
  • Uncover the drivers behind top-level KPIs: which behaviors, use cases and product experiences predict activation, retention and monetization.
  • Build what you need: data pipelines and models (SQL, dbt, Python, orchestration) that turn raw product, usage and billing data into trusted, reusable datasets.
  • Build and ship predictive models (conversion propensity, churn risk, usage forecasting, lead and account scoring) and bring their outputs into product and GTM workflows.
  • Design, run and evaluate experiments (A/B tests, pricing and packaging tests, onboarding changes) and apply causal inference where you can't run a clean experiment.
  • Proactively monitor key business and product metrics, investigate trends and anomalies, and surface insights stakeholders can act on.
  • Partner directly with the CEO and leadership on strategic questions, including pricing, growth levers, product bets and market opportunities, and turn ambiguous questions into clear analysis and decisions.
  • Set the standard for how we measure product success: metric definitions, a shared source of truth and analytical rigor across teams.

What We're Looking For (Must-Haves)

  • 5+ years of experience as a Product / Growth Analyst, Data Scientist or equivalent.
  • 2+ years in a SaaS company, with deep understanding of funnels, cohorts, activation, retention, monetization and PLG dynamics.
  • A strong statistical foundation.
  • A proven record of working end-to-end on your own, from data engineering through modeling to a delivered recommendation.
  • Strong hands-on experience using Python for data analysis, experimentation, machine learning and data modeling in a production environment.
  • Comfort working with large, messy, event-level datasets.
  • Hands-on experience building, validating and deploying predictive models (e.g., classification, forecasting, segmentation) that were used to make real business decisions.
  • Demonstrated ability to influence business strategy through data and drive alignment across cross-functional stakeholders, including executive leadership.
  • Strong communication: you can turn complex analysis into a clear, compelling story and a concrete recommendation.
  • Experience with modern data tooling (Snowflake/BigQuery, dbt, Airflow, and BI tools like Omni/Looker/Tableau).
  • BSc in Statistics / Math / CS or equivalent.

Nice to Have

  • Experience at an API-first, developer-focused or PLG company.
  • Experience with product analytics platforms (PostHog, Amplitude, Mixpanel).
  • Experience with pricing and packaging analysis or usage-based billing models.
  • Familiarity with LLMs / AI tooling, and using AI agents to speed up your own analytical work.
  • Evidence that you build things on your own: a GitHub profile, portfolio, side projects or publications.
  • MSc / PhD in Statistics / Math / CS or equivalent.

Pay Transparency

We offer competitive compensation and benefits packages. Actual compensation will be determined based on job-related factors, including experience, skills, qualifications, the level at which the candidate is hired, and geographic location, consistent with applicable law.

Base Compensation Range$179,000—$224,000 USDBenefits & Perks:

Competitive compensation

Career growth and learning opportunities

Flexibility and ownership

Collaborative and innovative culture

Opportunity to work on impactful AI projects

International environment and talented teams

What's it like to work at Nebius:

Fast moving - Bold thinking - Constant growth - Meaningful impact - Trust and real ownership - Opportunity to shape the future of AI 

Equal Opportunity Statement:

Nebius is an equal opportunity employer. We are committed to fostering an inclusive and diverse workplace and to providing equal employment opportunities in all aspects of employment. We do not discriminate on the basis of race, color, religion, sex (including pregnancy), national origin, ancestry, age, disability, genetic information, marital status, veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by applicable law.

Applicants must be authorized to work in the country in which they apply and will be required to provide proof of employment eligibility as a condition of hire. 

If you need accommodations during the application process, please let us know.

Source: Nebius careers

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