About the Role
The Lead Data Scientist will report to the Data Science Manager and be responsible for building and owning end-to-end pricing systems. This includes everything from experimentation to production, directly influencing revenue and unit economics. The role involves leading high-impact pricing experiments and applying advanced methods to understand key drivers of conversion, retention, and profitability. You will act as a subject matter expert in pricing and demand modeling, guiding strategy across Product, Risk, Finance, and Marketing.
Responsibilities
- Build and own end-to-end pricing systems—from experimentation to production—that directly shape revenue and unit economics.
- Lead high-impact pricing experiments and apply advanced methods to uncover what truly drives conversion, retention, and profitability.
- Act as a go-to expert in pricing and demand modeling, influencing strategy across Product, Risk, Finance, and Marketing.
- Drive cross-functional initiatives from idea to launch, partnering closely with engineering to deliver scalable, real-world solutions.
- Turn complex analyses into clear, compelling insights that guide leadership decisions.
- Mentor teammates and help raise the bar on experimentation, modeling, and technical rigor.
Requirements
- 6+ years of experience in data science, pricing, or quantitative modeling (or an advanced degree with relevant experience).
- Strong fluency in Python/R and SQL.
- Proven ability to build and ship pricing or demand models that drive real business impact, with comfort owning problems end-to-end.
- Deep expertise in pricing optimization, elasticity, and econometrics, and knowledge of how to apply causal inference and experimentation in real-world settings.
- Ability to thrive in cross-functional environments, influencing partners and translating complex work into clear, actionable insights.
- Enjoy mentoring others and raising the bar for how teams approach modeling, experimentation, and decision-making.
Even Better
- Experience in fintech, lending, or financial services with ownership of pricing models.
- Familiarity with financial metrics, risk-adjusted returns, and capital markets.
- Experience working with cloud platforms and modern data tools (e.g., AWS, DBT, Airflow, Looker).
- Exposure to LLMs or NLP applied to pricing or financial use cases.