This principal data science role leads hands-on data science and AI/ML delivery for a large-scale federal data modernization program, combining technical leadership with people management for a team of 3-5 engineers. The position is based in Columbia, Maryland with remote work options.
Responsibilities
- Lead data science work across structured and unstructured program data, including data collection, processing, cleaning, profiling, and preparation for analysis and modeling on a governed data platform.
- Design, develop, train, evaluate, and refine machine learning models and AI services, selecting algorithms and techniques aligned with customer and mission needs.
- Support deployment, monitoring, and maintenance of model performance in cloud environments using model lifecycle management, model serving, vector search, model evaluation, and related MLOps tooling.
- Deliver capabilities across internal AI tracks such as AI assisted schema tagging, automated code review, documentation generation, and ticket automation, plus user facing AI services for customers (AI assistants, conversational analytics, document grounded search, and approved retrieval augmented generation services).
- Operate within the program's AI governance intake and review process, registering production and pilot AI use cases before deployment, routing endpoints through a governed AI gateway, and maintaining inference logging, PII guardrails, rate controls, and human oversight and escalation paths.
- Plan and conduct proofs of concept and capability gate evaluations to assess accuracy, governance integration, cost, operational overhead, and policy alignment prior to scaling new AI capabilities.
- Embed responsible AI and equity requirements, including risk and impact assessments, bias testing across demographic and programmatic subgroups, plain language limitations and escalation paths, and periodic bias and drift re-reviews.
- Collaborate with ML engineers, data engineers, platform teams, and cross functional partners to develop and maintain the infrastructure and governed cloud environment needed for AI/ML operations.
- Create and maintain documentation for methodologies, code, assumptions, experiments, evaluation artifacts, and decisions, including SBOM documentation for AI tools to support reproducibility and governance review.
- Communicate technical findings, strategic vision, risks, tradeoffs, and business value to leadership and key stakeholders, and provide people management support and day-to-day technical guidance to a team of 3-5 engineers.
Requirements
- Master's degree in computer science, data science, statistics, mathematics, or a related field.
- 12+ years of experience in data analysis, data modeling, data profiling, and data management, with strong analytical and problem-solving skills.
- Deep understanding of CMS policies, regulations, and security and privacy expectations, with direct experience in Medicaid, CHIP, or comparable federal data and reporting programs.
- All candidates must pass public trust clearance through the U.S. Federal Government; this requires either U.S. citizenship or clearance through the Foreign National Government System with residence in the United States for at least 3 of the past 5 years, and a valid passport plus visa/work permit documentation.
- Strong experience with exploratory data analysis (EDA), feature engineering, analysis, and visualization across structured and unstructured data.
- Strong experience with machine learning modeling, including framing business problems, selecting model approaches, training models, evaluating performance, and interpreting results.
- Proficiency in at least one programming language or data platform such as Python, PySpark, R, SQL, Scala, Java, or C++, and experience with common machine learning frameworks and libraries.
- Experience with big data technologies, distributed processing, and data science toolsets, and experience using source control and CI/CD pipelines to support version control, collaboration, testing, and repeatable delivery.
- Excellent written and verbal communication skills, including the ability to explain complex technical concepts to both technical and non-technical audiences.
- Knowledge of sensitive government data handling, approved data-use practices, least-privilege access, privacy-aware data publication, public data controls, cell suppression, and Section 508/WCAG considerations for public-facing data products.
- Ability to comply with customer-specific security, privacy, accessibility, quality, training, and data-handling requirements for assigned systems and data.
Technologies
- Python
- PySpark
- R
- SQL
- Scala
- Java
- C++
- Databricks
- AWS
Benefits
- Medical, dental, and vision coverage
- 401(k) retirement benefits
- Paid time off
- Paid holidays
- Life and disability insurance
- Wellness and employee support programs
eSimplicity offers a comprehensive benefits package, including medical, dental, and vision coverage, 401(k) retirement benefits, paid time off, paid holidays, life and disability insurance, and additional wellness and employee support programs. Eligibility may vary based on employment status and applicable plan terms.
Preferred Qualifications
- Experience supporting federal, public sector, healthcare, or other regulated data, analytics, oversight, reporting, or public transparency programs.
- Experience with natural language processing (NLP), computer vision (CV), deep learning, and neural networks.
- Knowledge of retrieval augmented generation patterns, vector search, conversational analytics experiences, and AI gateway or governed endpoint patterns.
- Familiarity with machine learning infrastructure and AI/ML operational environments, including model lifecycle tooling, model serving, model evaluation, automated machine learning, AI observability, and metadata prerequisites for responsible AI expansion.
- Hands-on experience developing and deploying machine learning workloads within the Databricks platform or comparable modern cloud platforms such as AWS.
- Understanding of software development principles and best practices, including infrastructure as code and observability tooling.
- Preferred certifications may include Databricks Machine Learning, AWS Machine Learning or Data Analytics, SAFe, or related AI/ML and data platform credentials.
Working Environment
This is a remote position supporting Eastern Time business hours. Employees are expected to work 9:00 AM to 5:00 PM ET unless otherwise directed by their manager. Occasional travel for training or project meetings may be required and is estimated at less than 5% annually.
Reasonable Accommodation
eSimplicity is committed to providing reasonable accommodations to qualified individuals with disabilities during the application and hiring process. Applicants who need assistance or an accommodation should contact Human Resources.
Equal Employment Opportunity
eSimplicity is an Equal Opportunity Employer, including disability and protected veteran status. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, protected veteran status, disability, or any other legally protected status.
