• Turn ambiguous business questions into clear, well-scoped analyses.

Cross-functional partnership and documentation

• Partner with engineering on data pipelines (AWS Glue, Lambda, EventBridge). Investigate and help resolve production database performance issues, such as ORM query patterns and indexing, alongside backend engineering.

• Write down your methods and decisions in Confluence or an equivalent shared space, as you go, so other teams can find your reasoning and build on it without asking you directly.

Systems & Skills

Required

• Bachelor’s degree in a related field, or equivalent practical experience, and 3+ years of experience with applied statistics or machine learning.

• Applied statistics: probability, hypothesis testing, and model evaluation across classification and regression/quantile models (for example, precision, recall, calibration, quantile coverage, and drift).

• 3+ years of experience with SQL and a relational database in a professional capacity. Docketly’s production database runs on MySQL/Aurora, about 400 tables.

• Python for data analysis and modeling: pandas, scikit-learn, and a gradient-boosting framework (XGBoost, LightGBM, or CatBoost). Our production model uses CatBoost-based quantile regression.

• Experience training and deploying at least one model to production, or on a cloud ML platform such as AWS SageMaker.

• Metabase or comparable BI tooling.

• Clear written and verbal communication with non-technical stakeholders.

Preferred

• Staged production rollouts (canary or phased release) with holdout comparisons to prove model impact before full release.

• AWS Glue, S3, Lambda, EventBridge, CloudFormation.

• Comfortable using AI coding tools such as Claude Code or GitHub Copilot to move faster on analysis and modeling work.

• Experience diagnosing production database performance issues, such as query plans, indexing, and ORM-generated query patterns, in a large, high-table-count schema.

• Software-engineering practices applied to ML code, such as automated testing with pytest, for production pipelines.

Benefits

• Health, Dental, and Vision Insurance

• 401(k) with Company Matching

• Paid Time Off

• 7 Paid Company Holidays

• 4 Floating Holidays per Year

• Life Insurance and AD&D Insurance

• Long-Term Disability

• Health Care Reimbursement Flexible Spending Account (FSA)

• Dependent Care Flexible Spending Account

• Employee Assistance Program (EAP)

• Pet Insurance

Schedule & Location

Schedule: Monday-Friday, 8:00 AM-5:00 PM (Mountain Time) in Longmont, CO.

Salary Range: $110,000-$130,000 depending on experience

Application closing date: November 20, 2026, at 11:59pm