Senior Product Analyst / Data Scientist

The role:

In Token Factory analytics there is no split into product analysts, ML engineers and data engineers. Each person owns a question end to end: builds the data, runs the analysis, and comes back with a recommendation that changes a decision.

Your responsibilities will include:

- Define core product and business metrics and build a single source of truth that Product, Finance, and Sales can rely on.

- Build a comprehensive view of self-service customers, including usage patterns, customer health, satisfaction, retention risks, unmet needs, and growth opportunities.

- Translate customer demand and commercial plans into capacity forecasts and support capacity allocation decisions.

- Measure effective capacity utilization and identify opportunities to improve the commercial value of available capacity.

- Develop and evaluate pricing and packaging models, including guaranteed capacity, on-demand pricing, commitments, clawback mechanisms, and provisioned throughput units.

- Provide data-driven recommendations for the self-service and managed offerings, including customer segmentation, pricing, and capacity.

- Partner with Product, Engineering, Applied AI, Finance, and Sales to turn insights into concrete product and operational improvements.

We expect you to have:

- 5+ years of experience in analytics or data science.

- Strong Python, SQL, and statistics: you understand the code and the methods you use.

- Hands-on experience analysing large-scale customer, product, and usage datasets using statistical / analytical or distributed data-processing tools.

- AI-assisted coding as your default way of working: you guide it, verify it, and own the result.

- The ability to go from a question to a production-ready solution.

- The ability to turn complex data into clear recommendations.

- Strong commercial and product judgment, with the ability to balance customer value, monetization, growth, and profitability.

- Experience with pricing, packaging, monetization, or commercial analytics for technical or consumption-based products.

- Strong cross-functional collaboration skills across Product, Engineering, Data, Finance, Sales, and Operations.

- A hands-on and proactive working style, with the ability to operate effectively in an ambiguous and technically complex environment.

Nice to have:

- Familiarity with LLM inference economics: tokens, throughput and latency, batching, GPU costs.