> Markdown version of [/jobs/ext/3959934-lead-data-scientist](https://www.wearedevelopers.com/jobs/ext/3959934-lead-data-scientist). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md).

---

# Lead Data Scientist

- **Company:** Harnham Inc.
- **Location:** Tempe, AZ, United States
- **Experience:** Expert
- **Salary:** $140,000.0 - $150,000.0
- **Contract:** Permanent contract
- **Skills:** Amazon Web Services, Amazon S3, Database Queries, Python (Programming Language), Freeform SQL, Snowflake, Model Validation, Information Technology, Xgboost
- **Published:** October 27, 2026
- **Apply:** https://www.thejobnetwork.com/job/777c047c-1638-4f7d-ad04-e1291206a0e5/lead-data-scientist

## About the Role

Financial or risk modeling experience within a regulated industry is required, including direct experience defending models during external audits. Formal people management experience is not required., * Eight or more years of experience in data science, predictive analytics, quantitative analysis, or advanced risk modeling.
\n

 * Financial or risk modeling experience within a regulated industry.
\n

 * Direct experience supporting external model audits and defending model methodology and results.
\n

 * Advanced Python and SQL proficiency, including at least three years of experience developing models in Python and writing complex SQL queries.
\n

 * Experience with gradient boosting models, including XGBoost or CatBoost.
\n

 * Strong mathematical and statistical knowledge, including probability, sampling, predictive modeling, and model validation.
\n

 * Experience working with financial or credit datasets and translating findings into measurable business outcomes.
\n

 * Demonstrated ability to independently deliver projects from initial problem definition through implementation.
\n

 * Strong presentation skills, including experience communicating technical findings to executive audiences.
\n

 * A bachelor's degree in mathematics, statistics, economics, computer science, quantitative engineering, or a related discipline with substantial mathematical and statistical coursework.
\n, Relevant experience may include credit risk, credit loss assessment, probability of default modeling, scorecards, payment behavior, credit attributes, mortgages, credit cards, banking, or credit bureau data., * A master's degree in data science or another quantitative discipline. A business analytics master's degree alone does not replace the required mathematical and statistical foundation.
\n

 * Experience with portfolio risk management, loan scoring, or quantitative analysis of capital assets.
\n

 * Familiarity with model risk management practices and SR 11-7 guidelines.
\n

 * Experience with Snowflake and AWS services, including Amazon S3.
\n

 * Experience applying predictive analytics to residential real estate or related operational decisions., Applicants must be authorized to work in the United States without employer sponsorship now or in the future.