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

Nebius•New York, NY

1d•$179,000 - $224,000•Remote

About The Position

Nebius is seeking a senior, full-stack analyst / data scientist to own Product and PLG analytics end-to-end. This role involves owning the metrics behind the self-serve motion (signup, activation, usage, conversion, expansion, and retention) and identifying the drivers behind them. The successful candidate will act as a thought partner to the CEO and leadership on product and growth decisions. This is a fully independent role where the analyst will manage the entire process from building pipelines and modeling data to training and deploying models, analyzing results, and providing clear recommendations. Collaboration with other analysts, Product, Engineering, Growth, Marketing, and GTM teams is also expected.

Requirements

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 Haves

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.

Responsibilities

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 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.