FloatMe
Linkedin · Posted 1mo ago
Senior/Staff Data Scientist
Continue to application
Add your email once, then Caio opens the original posting.
Indexed description
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
- 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
Create a free Caio profile to unlock more results and save your role and location preferences.
Unlock free search
Want help applying to roles like this?
Search Caio for free. If repetitive applications get heavy, Managed Job Search adds supervised execution for $99/month.
View Managed Job Search