C. Mack Solutions is seeking a Senior Data Scientist to join AI/ML prototyping teams supporting a mission-critical Federal Government program. You will apply statistics, machine learning, and generative AI — including Google Gemini — to a variety of AI/ML pilot projects and use cases, turning complex operational data into models, insights, and recommendations that support mission decisions. You will work alongside AI/ML engineers and full stack developers who integrate your models into working applications, in a fast-moving Agile environment that delivers working software on short timelines.
This is a senior, hands-on role for someone who can frame an ambiguous problem, build and validate a sound analytical solution with little direction, and explain the results — and their limits — to technical and non-technical stakeholders.
As a Senior Data Scientist, here's what you'll be doing:
Analytics & Modeling
• Frame mission and business questions as analytical or machine learning problems, and define success measures with stakeholders and product owners
• Explore, clean, and prepare structured and unstructured data from SQL and NoSQL sources; engineer features suited to the problem
• Develop, train, validate, and tune statistical and machine learning models (e.g., classification, regression, clustering, anomaly detection, time-series forecasting) for AI/ML pilots and predictive analytics
• Evaluate model performance using appropriate metrics, validation strategies, and error analysis, and monitor deployed models for drift and bias
Generative AI
• Apply large language models, including Google Gemini, to use cases such as summarization, extraction, classification, and retrieval-augmented generation (RAG)
• Design prompts, grounding data, and evaluation sets, and build repeatable evaluation approaches for GenAI outputs (accuracy, consistency)
Delivery & Collaboration
• Partner with AI/ML engineers and developers to integrate models into applications through APIs, and help move promising prototypes toward production using sound MLOps practices (versioning, reproducibility, deployment, monitoring)
• Communicate findings through clear visualizations, dashboards, and briefings, including uncertainty and limitations
• Document data sources, methods, assumptions, and model behavior to support reproducibility, governance, and responsible-AI review
• Act as a member of one or more prototyping teams, supporting teammates and collaborating to deliver working software applications on short timelines
• Analyze complex project-related problems and create innovative solutions involving technology, methodology, tools, and solution components
• Actively participate in Agile delivery phases and ceremonies, including release and sprint planning, artifact creation, sprint testing, demonstrations, and retrospectives
• Work independently on complex tasks with little direction and management oversight, and mentor less experienced team members
Requirements
You must live within the DC, MD, VA area.
U.S. Citizenship is required. Candidate must be able to obtain a CBP Public Trust clearance.
• Bachelor’s degree (BA/BS) in Data Science, Statistics, Mathematics, Computer Science, or a related quantitative field
• 7+ years of experience in data science, machine learning, or a related quantitative/analytical role
• Strong proficiency in Python and its data science stack (e.g., pandas, NumPy, scikit-learn, Jupyter), and experience with at least one deep learning framework (PyTorch or TensorFlow)
• Strong SQL skills, and experience working with NoSQL data stores (e.g., MongoDB, DynamoDB)
• Solid foundation in statistics, including probability, regression, hypothesis testing, sampling, and experimental design
• Hands-on experience building and evaluating machine learning models end to end, from data preparation through validated results
• Practical generative AI experience: working with LLMs, prompt engineering, embeddings/RAG, and evaluating LLM outputs
• Experience with data visualization (e.g., matplotlib, seaborn, Plotly) and/or BI tools (e.g., Tableau, Power BI, Looker)
• Experience working with APIs and common data formats (JSON, YAML) to access data and deliver model results
• Ability to analyze technically complex problems and develop and implement new and innovative solutions in a fast-moving, fluid software prototyping environment
• Excellent written and verbal communication skills, including the ability to explain technical results to non-technical stakeholders
Preferred Skills and Experience:
• Google Gemini and Google Cloud Vertex AI experience strongly preferred; experience with AWS SageMaker or Bedrock also valued
• Master’s or Ph.D. in a quantitative field
• Experience working with live data and video streams; computer vision experience a plus
• MLOps experience (e.g., MLflow, model registries, containerized deployment with Docker) and CI/CD solutions such as GitLab
• Experience with large-scale data processing tools such as Spark, Databricks, or BigQuery
• Experience with geospatial or sensor data
• Familiarity with responsible-AI practices and federal AI risk management (e.g., NIST AI Risk Management Framework)
• Technical certifications such as Google Cloud Professional Machine Learning Engineer, AWS Certified Machine Learning Engineer – Associate, or AWS Certified AI Practitioner
• Federal experience, ideally within DHS or a law enforcement / regulated environment
• Experience working in a geographically dispersed, remote team
Work Location: This position is limited to candidates residing in U.S. states where the company is currently registered to employ team members.
Salary Range: $125,000 – $175,000 annually
This position may be filled at the Mid, Senior or SME level based on the selected candidate’s qualifications and experience. Final compensation will be determined based on level alignment, experience, education, and internal equity.
Benefits: In addition to base compensation, this position is eligible for company-sponsored benefits, which may include medical, dental, and vision insurance, retirement savings plans, paid time off, and other supplemental programs.