Senior Data Scientist

Blueflag-LLP; Raleigh (NC); Sur place; USD 150 000 - 190 000; Plein temps

Avantages offerts par ce poste

Competitive salary

401(k) with company match

Health insurance

Résumé du poste

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.

Responsabilités

• 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.

Connaissances

Python

PySpark

SQL

ML/DL

Model deployment

Experiment tracking

Big data

Formation

Master's/PhD

Outils

Databricks

MLflow

Azure

Git

Unity Catalog

Delta Lake

Description du poste

BlueFlag is looking for a Senior Data Scientist to support a premier data and AI platform for the Department of Veterans Affairs. You'll work directly with internal clients to turn operational problems into production machine learning and AI solutions on Databricks in Azure, and help their teams adopt modern cloud tooling. This role is hands‑on. We want someone who has taken models from a notebook to production and kept them running.

What You'll Do

• Consult with internal clients to frame business problems as analytical or ML problems, define success metrics, and set realistic scope
• Build data products and workflows that support critical operations, from source data discovery through production deployment
• Migrate and modernize client workloads from legacy environments (including R, Stata, and SAS) to Python and Databricks, with measurable gains in runtime, cost, or reliability
• Develop, train, and validate ML models (classification, regression, forecasting, clustering, anomaly detection) for complex business problems
• Engineer features and build reusable, governed feature pipelines on large datasets with PySpark and SQL
• Track experiments, register models, and manage model versions and promotion through MLflow
• Deploy models for batch scoring and real‑time serving, and automate retraining with scheduled jobs and CI/CD pipelines
• Monitor models in production for performance, data drift, and data quality, and set thresholds and alerts that trigger review or retraining
• Lead AI adoption with clients, including LLM and agentic use cases such as retrieval‑augmented generation (RAG), document summarization, and classification
• Evaluate LLM and agent outputs for accuracy, groundedness, and safety before and after release
• Document models (purpose, data, assumptions, limitations, evaluation results) so they hold up to governance and responsible AI review
• Build reference use cases with tutorials, reference code, and training to drive adoption of cloud tooling for concrete business results
• Host office hours and pair with client analysts and data scientists to upskill them
• Present findings and model results clearly to technical and non‑technical audiences, including leadership

Why Join BlueFlag

At BlueFlag, we’re passionate about leveraging cutting‑edge technology to make a real difference. You’ll be at the forefront of cloud innovation, working on projects that directly impact people’s lives. We offer a high‑growth, entrepreneurial environment that values fresh ideas and authentic teamwork.

If you’re ready to take your data engineering career to new heights and contribute to meaningful projects that push the boundaries of technology, we want to hear from you. Join BlueFlag and be part of a team that’s shaping the future of AI solutions!

• Bachelor's degree in Engineering, Computer Science, Statistics, Mathematics, Systems, Business, or a related scientific or technical discipline, and 15+ years of experience (or commensurate experience)
• Proficient in Python (pandas, NumPy, SciPy, scikit-learn) and advanced SQL (window functions, CTEs, query tuning) for data analysis
• 2+ years of hands‑on work on a leading cloud data platform such as Databricks, Azure, AWS, or GCP
• Experience across the end-to-end data science workflow, from finding and assessing datasets to production deployment, including experiment tracking and model management with MLflow or similar
• Solid grounding in traditional machine learning: supervised and unsupervised methods, gradient‑boosted trees (XGBoost, LightGBM), model selection, cross‑validation, and hyperparameter tuning
• Strong applied statistics: hypothesis testing, regression, sampling, and experimental design
• Experience working with large datasets in a distributed environment (Spark/PySpark)
• Sound model evaluation practice: picking the right metrics, handling class imbalance, avoiding leakage, and explaining model behavior (for example SHAP or feature importance)
• Working knowledge of large language models (LLMs) and agentic AI workflows, including prompt design and RAG patterns
• Version control with Git and collaborative development practices (code review, branching, testing)
• Ability to explain technical work to non‑technical stakeholders and turn ambiguous requests into defined deliverables

• US Citizen: Must be a citizen of the United States
• Security Clearance: Must be able to obtain a public trust clearance. Must be eligible to work in the United States.

Desired

• 5+ years as a data scientist, shipping multiple products that run in operation
• Working experience with Databricks in Azure, including Unity Catalog, Delta Lake, Databricks Jobs, and Databricks notebooks/Repos
• MLOps experience across the lifecycle, such as:
  • Model Serving endpoints for real‑time inference
  • Feature engineering and feature tables governed in Unity Catalog
  • CI/CD for ML with Azure DevOps or GitHub Actions, and Databricks Asset Bundles
  • Production monitoring for drift and model quality (for example Lakehouse Monitoring)
  • Champion/challenger or A/B testing of models in production
  • Automated retraining and model lineage and auditability
• Experience with Azure AI services (Azure OpenAI, Azure Machine Learning) or Mosaic AI (Vector Search, Agent Framework)
• Prior experience shipping products that use LLMs or AI agents, including evaluation and guardrails
• 2+ years building visual insights (dashboards and reports) that support operational needs, with Power BI, Databricks AI/BI dashboards, or Tableau
• Prior experience with R, Stata, or SAS
• Experience refactoring R, Stata, or SAS codebases to Python, including validating that results match
• Experience with VA or federal healthcare data, and handling PHI/PII under federal privacy and security requirements
• Familiarity with federal AI governance and responsible AI practices (bias testing, model documentation, human oversight)
• Experience training or mentoring analysts and data scientists
• Master's or PhD in a quantitative field

• Competitive salary
• Generous annual leave and paid holidays
• Comprehensive group health and dental plans
• 401(k) with company match
• Life insurance and AD&D coverage
• Ongoing training and professional development opportunities