The Role
Lead end-to-end experimentation and analytics for the fintech product: design A/B and multivariate tests, measure impacts on behavior, unit economics, and risk; turn model outputs into business rules; define metrics and dashboards; partner with product, finance, risk, and engineering; and communicate results to non-technical stakeholders.
Summary Generated by Built In
Most people earn money every day, but only see it hit their account every few weeks. We’re a fintech company focused on modernising how workers access and manage their pay, giving them more flexibility and control over their cash flow.
Our platform plugs into the tools employers already use—timekeeping, workforce, and payroll systems—so employees can see and use what they’ve earned without changing how they work today. Think of it as an intelligent layer on top of existing infrastructure that turns static pay cycles into dynamic, real-time experiences.
Role: Product Data Scientist
We’re hiring a Product Data Scientist to own the measurement, experimentation, and analytics that shape both the product experience and how we think about credit and risk. You’ll design how we test ideas, define whether they’re successful, and ensure that decisions across the company are grounded in clear, quantitative evidence rather than gut feel.
This role is squarely in the “analytics + experimentation” lane: it’s about structuring tests, analysing outcomes, and influencing strategy, not building large-scale ML systems from scratch. You’ll sit between product, finance, risk, and engineering, helping each function understand the impact of changes on growth, economics, and portfolio quality.
Responsibilities
Own the end-to-end experimentation framework for the product, from ideation and design through implementation and readout.
Design A/B and multivariate tests that touch both user-facing surfaces and credit policies, and quantify their impact on behaviour, economics, and risk.
Turn risk indicators and model outputs into practical business rules and strategies for approvals, exposure, and pricing.
Act as the central source of truth for experiment results, setting standards for methodology, guardrails, and interpretation.
Define core product and financial metrics, and build dashboards and frameworks to monitor behaviour, unit economics, and overall performance.
Partner with Product, Finance, Risk, and Engineering to evaluate trade-offs and make calls that balance user value, growth, and portfolio health.
Serve as a strategic thought partner, clearly communicating what the data says (and doesn’t say) to non-technical stakeholders.
Minimum Requirements
Approximately 5+ years in data science, product analytics, or another quantitative role with direct impact on product or business strategy.
Strong foundation in statistics and experimental design, including A/B testing, hypothesis testing, and practical causal inference concepts.
Hands-on experience running structured experimentation programs and using their results to shape roadmaps or policies.
Deep SQL proficiency and comfort working with large, messy datasets.
Ability to translate complex analyses into clear, concise narratives and recommendations for business and product leaders.
History of successful collaboration with cross-functional teams in fast-moving environments.
Strong business intuition, with a habit of thinking in terms of unit economics, trade-offs, and risk-versus-growth dynamics.
Nice-to-Have Experience
Exposure to fintech, lending, or credit products, especially around risk scoring or portfolio management.
Familiarity with underwriting concepts like approval strategies, loss expectations, and credit performance measurement.
Experience building forecasting or projection models for revenue, engagement, or portfolio metrics.
Proficiency in Python or R for data analysis and experiment evaluation.
Hands-on use of experimentation platforms and statistical tooling in a production environment.
Requirements
Work Setup & Compensation
- Hybrid role in NYC, with regular in-office collaboration several days per week.
- Competitive base salary aligned with senior individual-contributor data roles in fintech, plus equity and a full benefits package.
Benefits & Perks
- Comprehensive health coverage (medical, dental, vision) with options for dependents.
- Paid parental leave and employer-supported retirement plans.
- Flexible PTO policy tailored for salaried roles.
- Stipend for home office setup and remote collaboration tools.
- Access to the company’s products and financial wellness tools for your own use.
Skills Required
- Approximately 5+ years in data science, product analytics, or another quantitative role with direct impact on product or business strategy
- Strong foundation in statistics and experimental design, including A/B testing, hypothesis testing, and causal inference concepts
- Hands-on experience running structured experimentation programs and using results to shape roadmaps or policies
- Deep SQL proficiency and comfort working with large, messy datasets
- Ability to translate complex analyses into clear, concise narratives and recommendations for business and product leaders
- History of successful collaboration with cross-functional teams in fast-moving environments
- Strong business intuition, with a habit of thinking in terms of unit economics, trade-offs, and risk-versus-growth dynamics
- Hybrid role in NYC with regular in-office collaboration several days per week
- Exposure to fintech, lending, or credit products (risk scoring or portfolio management)
- Familiarity with underwriting concepts like approval strategies, loss expectations, and credit performance measurement
- Experience building forecasting or projection models for revenue, engagement, or portfolio metrics
- Proficiency in Python or R for data analysis and experiment evaluation
- Hands-on use of experimentation platforms and statistical tooling in a production environment
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The Company
What We Do
Calliere is a boutique professional and executive recruitment and advisory firm that helps organizations build high-performance teams. It specializes in sourcing leadership, engineering, data science and AI, healthcare technology, infrastructure, telecom, sales, and business-development talent. The firm serves clients across technology, fintech, healthcare, life sciences, infrastructure, and other sectors through a personalized, thorough, results-driven approach tailored to each client's specific hiring and organizational needs.
