Senior Data Scientist

BlueFlag LLC; Austin (TX); On-site; USD 140,000 - 220,000; Full time

Benefits offered by this job

Competitive salary

Generous annual leave

Health plan

401(k) with company match

Life insurance

Job summary

BlueFlag is seeking a Senior Data Scientist to deliver production ML/AI solutions for a premier data platform. You’ll turn operational problems into scalable data products on Databricks in Azure, working directly with internal clients to drive measurable gains.

You will migrate workloads from legacy tools to Python, train and validate models, manage feature pipelines, and deploy solutions with CI/CD. Strong collaboration and governance are essential.

Qualifications

• Bachelor's degree in a STEM field and 15+ years of experience.
• Expert in Python (pandas, NumPy, SciPy, scikit-learn) and advanced SQL.
• 2+ years hands-on with a leading cloud platform such as Databricks/Azure/AWS/GCP.
• End-to-end DS workflow experience including experiment tracking and MLflow.
• Strong foundation in supervised/unsupervised learning and ML evaluation.
• Experience with Spark/PySpark and handling large datasets.

Responsibilities

• Consult with internal clients to frame problems and define success metrics.
• Build data products and workflows from data discovery to production.
• Migrate workloads from legacy environments to Python and Databricks.
• Develop, train, and validate ML models for complex problems.
• Engineer feature pipelines and manage model versions with MLflow.
• Deploy models for batch and real-time scoring, with CI/CD pipelines.
• Monitor production models for data drift and quality; set alerts.
• Lead AI adoption, including RAG and document summarization use cases.
• Evaluate LLM outputs for accuracy and safety before release.
• Document models for governance and responsible AI review.
• Develop reference use cases and tutorials to drive cloud tooling adoption.
• Host office hours and upskill client analysts and data scientists.
• Present findings clearly to technical and non-technical audiences.

Skills

Python programming

Pandas/NumPy

Scikit-learn

Advanced SQL

ML model development

PySpark

Model evaluation

Communication with clients

Education

Bachelor's degree in Engineering, CS, Statistics, Math, Systems, or related

Tools

Databricks

Azure

SQL tooling

Git

Job description

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!

Requirements

• 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

Benefits

• 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