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

**Company**: Nebius
**Location**: New York City, New York
**Experience**: senior
**Job type**: full-time
**Salary**: $179,000-$224,000 USD
**Category**: Data Science
**Industry**: Technology

**Apply**: https://job-boards.greenhouse.io/nebius/jobs/4989979101?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply
**Canonical**: https://yubhub.co/jobs/job_447c716b-6b4

## Description

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.

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 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.

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 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.

Benefits & 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

## Skills

### Required
- Python
- SQL
- dbt
- data analysis
- experimentation
- machine learning
- data modeling
- predictive models
- statistical foundation

### Nice to have
- Experience at an API-first, developer-focused or PLG company
- product analytics platforms
- pricing and packaging analysis
- usage-based billing models
- LLMs / AI tooling

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Source: [Apply at job-boards.greenhouse.io](https://job-boards.greenhouse.io/nebius/jobs/4989979101?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply)