102516 - Sr. Data Scientist B. at resilientco

Clearco is a leader in AI and data-driven eCommerce funding, providing non-dilutive capital that helps founders grow without sacrificing equity. We are hiring a Senior Data Scientist to shape the models, experiments, and analytics that drive our risk, underwriting, and revenue decisions. This hands-on senior role sits at the intersection of Data Science, Machine Learning, and Product. You will partner with Engineering, Product, Risk, and Finance to turn ambiguous problems into production-grade models and measurable outcomes that responsibly scale funding for eCommerce businesses. Responsibilities • Design and execute data science experiments, including causal analysis, A/B tests, and offline evaluation. • Develop, evaluate, and iterate on predictive models for credit/risk scoring, revenue forecasting, and 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 with emphasis on reliability, reproducibility, and maintainability. • Perform exploratory data analysis, feature engineering, and robust validation on real-world, messy data. • Communicate insights and recommendations clearly to technical and non-technical stakeholders through documentation and presentations. • Improve analytical standards, code review practices, and documentation to raise technical quality. • Mentor and support team members through pairing, feedback, and sharing best practices. Requirements • 5+ years of professional experience in data science, applied machine learning, or a related quantitative role. • Strong foundations in statistics and experimentation, including hypothesis testing, causal reasoning, and evaluation design. • Proven experience building and shipping predictive models (classification, regression, time series) and measuring real-world impact. • Strong proficiency in Python and SQL and comfort working with production data workflows. • Experience defining success metrics, aligning with stakeholders, and delivering end-to-end outcomes. • Strong written communication skills and a pragmatic approach to fast-moving environments. • Experience owning model performance, monitoring for drift, and improving feature reliability. Nice to have • Experience with credit risk, underwriting, fraud/risk signals, or financial forecasting. • Experience with modern data tooling and warehouses such as BigQuery or Snowflake and transformation frameworks like dbt. • Familiarity 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).