Pay
Higher than most similar jobs
$179K–$224K against $118K–$193K, the middle half of what similar US postings state.
From 3,721 postings in the last year. Stated ranges, not salaries paid.
Senior Product & PLG Analyst (Full-Stack Data Scientist)
New York City, New York, United States
Live, first seen by us 19 days ago- Pay
USD 179,000–224,000/year · BaseAnnual period assumed — pay source
Base Compensation Range $179,000—$224,000 USD Benefits & Perks:
Read the full posting- Work setting
- Not stated
- Employment
- Not stated
What you’ll work on
Full postingWe're looking for a senior, full-stack analyst / data scientist to own Product and PLG analytics end-to-end.
Define, instrument and measure the self-serve funnel from first API call to expansion and churn
Find which behaviors and use cases predict activation, retention and monetization
Build data pipelines and models that turn raw product, usage and billing data into trusted datasets
Build and ship predictive models such as conversion propensity and churn risk
Design and evaluate experiments such as A/B tests and pricing tests
From the employer’s posting
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.
define, instrument and measure the self-serve funnel, from first API call through activation, conversion to paid, expansion and churn
which behaviors, use cases and product experiences predict activation, retention and monetization
Build what you need: data pipelines and models (SQL, dbt, Python, orchestration)
Build and ship predictive models (conversion propensity, churn risk, usage forecasting, lead and account scoring)
Design, run and evaluate experiments (A/B tests, pricing and packaging tests, onboarding changes)
Education & alternatives
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
About Nebius
Nebius is leading a new era in cloud infrastructure for the global AI economy.
In the employer’s words · Read in context
Posting record
Report an error- Status in our records
- Live
- First seen by us
- Oct 15, 202619 days ago
- Recorded sightings
- 76
- Last seen by us
- Nov 4, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
How this job compares
Time since we first saw it
Day 19
Similar jobs usually come down between day 7 and day 55.
From 9,971 similar postings that came down. Coming down is not always a hire.
Nebius is hiring
17 open jobs
Open jobs by the week we first saw them, last 12 weeks.
- Hiring at a steady pace
- Its jobs tend to stay up a long time
- 12% of open jobs were reposted
See how this role fits your experience
Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
- Python
- SQL
- BigQuery
- dbt
- Looker
- Snowflake
- Tableau
- Airflow
Where the posting names them
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)
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
Your next step
Complete your application on careers.nebius.com. The employer’s form will show what is required.
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Already applied? Track this application
About the role
We file this job under Data Scientist, by the work the posting describes.
Data scientists use statistics and models to answer harder questions, such as whether a change worked, what demand will look like next quarter, or which customers are likely to leave.
Postings usually ask for Python or R, SQL, statistics, experiment design and common machine learning methods.
Unlike an ML engineer, a data scientist's main output is often an analysis or a first model, not software running inside a product.
US government figures for data scientists
- Median yearly pay, May 2025
- $120,230
- Expected change, 2025 to 2035
- 34.6% more jobsagainst 3.5% for all jobs
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-2051.
Job description
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 USD
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
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.
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- Pay
Base Compensation Range $179,000—$224,000 USD Benefits & Perks:
- Location & working pattern
New York City, New York, United States
Working pattern and location restrictions need checking in the full posting.
- Work authorization
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.