Senior Data Scientist – Production ML on Azure/Databricks

Blueflag-LLP; Salt Lake City (UT); On-site; USD 120,000 - 190,000; Full time

Benefits offered by this job

Competitive salary

Generous annual leave

Comprehensive health and dental plans

401(k) with company match

Life insurance and AD&D

Job summary

BlueFlag is hiring a Senior Data Scientist to transform DoD data problems into production ML solutions on Databricks in Azure. You will collaborate with internal clients, frame business problems, and deploy models with CI/CD pipelines.

You’ll migrate legacy workloads (R, Stata, SAS) to Python, build scalable data products, track experiments with MLflow, and monitor model performance in production.

Qualifications

• Bachelor's degree in a quantitative field.
• 5+ years of data science experience shipping products in production.
• Experience with cloud data platforms (Azure, AWS, GCP) and Databricks.
• Proficiency in Python data stack (pandas, NumPy, SciPy, scikit-learn).
• Strong ML modelling (classification, regression, forecasting, clustering).
• Experience with MLflow or similar model management tools.

Responsibilities

• Frame business problems as analytics/ML challenges with clear success metrics.
• Build data products and workflows from data discovery to production deployment.
• Migrate legacy workloads to Python and Databricks with measurable gains.
• Develop, train and validate ML models for complex business problems.
• Engineer feature pipelines and ensure governance for large datasets.

Skills

Python

SQL

PySpark

Databricks

Azure

MLflow

Model deployment

Data storytelling

Education

Bachelor's degree

Master's/PhD preferred

Tools

Databricks

Power BI

Git

Job description

BlueFlag is hiring a Senior Data Scientist to transform DoD data problems into production ML solutions on Databricks in Azure. You will collaborate with internal clients, frame business problems, and deploy models with CI/CD pipelines.

You’ll migrate legacy workloads (R, Stata, SAS) to Python, build scalable data products, track experiments with MLflow, and monitor model performance in production.