Senior Data Scientist - Production ML on Azure/Databricks

Blueflag-LLP; Raleigh (NC); On-site; USD 150,000 - 190,000; Full time

Benefits offered by this job

Competitive salary

401(k) with company match

Health insurance

Job summary

BlueFlag is seeking a Senior Data Scientist to translate operational problems into production ML solutions on Databricks in Azure. You will work with internal clients, frame problems, and deploy models with CI/CD pipelines to production environments.

Responsibilities include building data products, migrating legacy workloads to Python, training and validating models, tracking experiments with MLflow, and monitoring performance. Collaboration with leadership is essential.

Qualifications

• 15+ years of data science experience or equivalent.
• Proficient in Python and advanced SQL for data analysis.
• 2+ years hands-on on a cloud data platform such as Databricks/Azure.
• End-to-end data science workflow from exploration to production.
• Experience with MLflow for experiment tracking and model management.
• Familiarity with large language models and AI workflows.
• Ability to explain complex technical work to non-technical stakeholders.

Responsibilities

• Consult with internal clients to frame problems and define success metrics.
• Build data products and workflows from discovery to production deployment.
• Migrate workloads from legacy environments to Python and Databricks.
• Develop, train, and validate ML models for complex problems.
• Engineer features and reusable pipelines on large datasets with PySpark and SQL.
• Track experiments and manage model versions with MLflow.
• Deploy models for batch scoring and real-time serving; automate retraining.
• Monitor models for drift and data quality; set review triggers.

Skills

Python

PySpark

SQL

ML/DL

Model deployment

Experiment tracking

Big data

Education

Master's/PhD

Tools

Databricks

MLflow

Azure

Git

Unity Catalog

Delta Lake

Job description

BlueFlag is seeking a Senior Data Scientist to translate operational problems into production ML solutions on Databricks in Azure. You will work with internal clients, frame problems, and deploy models with CI/CD pipelines to production environments.

Responsibilities include building data products, migrating legacy workloads to Python, training and validating models, tracking experiments with MLflow, and monitoring performance. Collaboration with leadership is essential.