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# Senior Data Scientist

- **Company:** SnapCommerce Inc.
- **Location:** United States (Remote available)
- **Experience:** Expert
- **Salary:** $121,000.0 - $181,000.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Data Analysis, Computer Programming, Statistical Hypothesis Testing, Machine Learning, NumPy, Tensorflow, Standard Sql, Pytorch, Deep Learning, Pandas, Scikit Learn, Information Technology, Data Analytics, Data Pipelines
- **Published:** August 9, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=d5dbbf7c556fbbea

## About the Role

* 5+ years of experience in data science roles, with a track record of shipping models that delivered measurable business impact
 * Demonstrated ability to own projects independently and lead others through technical ambiguity
 * Experience taking models to production and maintaining them (deployment, monitoring, retraining)
 * A technical degree in data science, computer science, analytics, or AI, or equivalent applied experience building and evaluating production models
 * Strong SQL, including the ability to build clean, performant transformations, ideally with DBT
 * Expert programming skills with fluency in the ML stack: sklearn, pandas, numpy, and a deep learning framework such as TensorFlow or PyTorch
 * Previous experience in fintech & lending

## Description

* Lead the design and delivery of statistical and machine learning solutions that drive high-impact, data-driven decisions across the business
 * Own complex, ambiguous problems end to end, from framing the question to deploying and monitoring the solution in production
 * Investigate trends, patterns, and anomalies at depth; diagnose root causes and surface opportunities that shape product and business strategy
 * Architect data pipelines to access, clean, and transform large, raw datasets, and establish reusable patterns others can build on
 * Design, implement & monitor business rules for cash flow underwriting and repayment workflows
 * Partner with product, engineering, and business leaders to translate strategic priorities into data science roadmaps and influence decisions at the leadership level
 * Proactively identify the highest-leverage problems worth solving, and build or scope the right solution rather than the obvious one
 * Design and run rigorous experimentation programs (A/B and beyond) to test hypotheses, measure product changes, and quantify business impact
 * Develop, prototype, validate, and productionize machine learning models and algorithms, balancing accuracy against latency, cost, and maintainability
 * Communicate technical findings and model results to senior and non-technical stakeholders through clear visualizations, writeups, and recommendations


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