Senior Data Scientist
$150k - $200kClearco
Clearco is the capital partner that thinks like a founder. We provide fast, flexible, and founder-first funding designed to scale with your momentum. With over $3 billion deployed to 10,000+ brands, Clearco is the only platform offering both Cash Advance and Invoice Funding in one place. Our performance-driven model delivers competitive terms, capped weekly repayments, and access to capital in as little as 24 hours. There's no dilution, no personal guarantees, and no friction. Whether you're securing inventory, funding ads, or launching your next big product, Clearco helps you move faster with confidence.
About the Role We are hiring a Senior Data Scientist to build and improve the models, analyses, and experimentation that power Clearco's risk and revenue decisions. This hands-on senior role is at the intersection of Data Science, Machine Learning, and Product. You will partner closely with Engineering, Product, Risk, and Finance teams to translate ambiguous problems into well-scoped analyses and production-grade solutions. Your work will influence how we assess risk, forecast performance, and responsibly scale funding for eCommerce businesses. What You'll Do- Design and execute data science experiments such as causal analysis, A/B tests, and offline evaluations to validate product and underwriting decisions.
- Develop, evaluate, and iterate on predictive models (e.g., credit/risk scoring, revenue forecasting, policy performance).
- Own model performance and monitoring: define success metrics, investigate drift, and drive improvements to data quality and feature reliability.
- Partner with Product Engineering to productionize models and analytics, focusing on reliability, reproducibility, and maintainability.
- Turn messy real-world data into usable signals through exploratory analysis, feature engineering, and robust validation.
- Clearly communicate insights to both technical and non-technical stakeholders through documentation and presentations.
- Raise the bar for technical quality via improved analytical standards, code review practices, and documentation.
- Mentor and support other team members through pairing, feedback, and sharing best practices.
- 5+ years of professional experience in data science, applied machine learning, or a related quantitative role
- Strong foundations in statistics and experimentation (hypothesis testing, causal reasoning, bias/variance tradeoffs, evaluation design)
- Proven experience building and shipping predictive models (classification, regression, time series, etc.) and measuring real-world impact
- Proficiency in Python and SQL, with comfort working with production data workflows
- Comfortable working with stakeholders to define problems, align on success metrics, and deliver outcomes end-to-end
- Strong written communication skills and a pragmatic approach to fast-moving environments
- Experience with credit risk, underwriting, fraud/risk signals, or financial forecasting
- Familiarity with modern data tooling and warehouses (e.g., BigQuery, Snowflake) and transformation frameworks (e.g., dbt)
- Experience with MLOps patterns (model deployment, monitoring, feature stores, orchestration) and cloud environments
- Experience working with messy third-party data sources (banking data, eCommerce platforms, marketing signals, etc.)
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