What are the responsibilities and job description for the Senior/Staff Data Scientist position at FloatMe?
FloatMe is hiring a Senior/Staff Data Scientist to turn product, customer, and risk data into the insights and decision frameworks that shape how we grow. You'll own end-to-end execution — analysis, experimentation, forecasting, visualization — and partner closely with our ML Engineers to evaluate model performance and connect risk decisions directly to business impact. If you love turning ambiguous, high-stakes questions into sharp, decision-ready answers and want to set the technical bar for a fast-moving fintech team, this is the seat for you.
What You’ll Do
Compensation Range: $150K - $220K
What You’ll Do
- You will turn complex product, customer, and risk data into clear insights, decision frameworks, and durable measurement systems for product, risk, and business partners
- Own end-to-end execution across analysis, metrics definition, experimentation, forecasting, visualization, and decision support
- Define and maintain measurement frameworks for FloatMe products, including customer eligibility, repayment behavior, product usage, loss performance, funnel health, subscription, and long-term customer outcomes
- Partner with Machine Learning Engineers (MLEs) to evaluate model and policy performance, monitor cohorts, identify bias or drift, and connect risk decisions to product and business impact
- Design and analyze experiments, rollouts, and policy changes that shape customer access, repayment outcomes, and product growth
- Approach ambiguous product and risk questions from first principles, using statistical judgment to define the right cohorts, metrics, and decision criteria
- Communicate insights clearly to technical, product, and business stakeholders, including risk partners and senior decision-makers
- Lead technical direction and standards - making and building consensus on key technical decisions, and creating reusable frameworks, measurement templates, and scalable tooling that remove complexity for others
- Drive localized cross-team impact by partnering with senior stakeholders in product, engineering, and risk to align Data Science work with broader strategy
- 4 years applying AI, machine learning, or statistical modeling in decisioning contexts such as credit, risk, fraud, recommendations, or similar domains.
- A Master degree in a quantitative field (e.g., Mathematics, Statistics, Physics, Computer Science, Operation Research). A PhD degree is welcomed.
- Advanced proficiency with SQL, Python and experience building clear, decision-oriented data visualizations
- Strong product, analytical, and statistical judgment, including the ability to turn ambiguous product, customer, or risk questions into sound analyses, communicate tradeoffs clearly, and support decisions
- Experience using AI tools to improve the speed, quality, and durability of analytical work
- Fintech background
- Consumer finance experience (non-large bank environment)
- Advanced modeling techniques
- Background in small to medium sized companies
Compensation Range: $150K - $220K
Salary : $150,000 - $220,000