Principal Data Scientist

About Us 

eSimplicity is a modern digital services company that partners with government agencies to improve the lives and protect the well-being of all Americans, from veterans and service members to children, families, and seniors. Our engineers, designers, and strategists cut through complexity to create intuitive products and services that equip federal agencies with solutions to courageously transform today for a better tomorrow. 

Position overview 

The Principal Data Scientist Lead will lead data science and AI/ML delivery for a large-scale federal data and analytics modernization program, combining hands-on data science, cloud-based AI/ML development, technical leadership, and people-management support for a team of 3–5 engineers. The program supports governed data assets, reusable analytics, dashboards, APIs, public-facing reporting, and AI-enabled services. 

This role will design, build, scale, and evaluate AI/ML pipelines and services on governed foundations, expanding AI capabilities only where metadata, lineage, controls, and evaluation are sufficient. The Principal Data Scientist Lead will translate model insights into actionable recommendations for leadership, stakeholders, and production implementation across internal delivery-acceleration and user-facing AI service tracks. 

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 appropriate algorithms and techniques for specific 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 both program AI tracks: internal AI-enabled delivery acceleration (AI-assisted schema tagging, automated code review, documentation generation, ticket automation) and user-facing AI services for customer users and approved consumers (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 all production and pilot AI use cases before deployment, routing managed endpoints through a governed AI gateway layer, and maintaining inference logging, PII guardrails, rate controls, and human oversight and escalation paths. 
• Plan and conduct proofs of concept and capability-gate evaluations that assess accuracy, governance integration, cost, operational overhead, and alignment to customer policy before scaling new AI capabilities. 
• Embed responsible AI and equity requirements into delivery, including algorithmic risk and impact assessments, bias testing across relevant demographic and programmatic subgroups, plain-language limitations and escalation paths, and periodic bias and drift re-review. 
• Collaborate closely with ML engineers, data engineers, platform teams, and cross-functional partners to develop and maintain the infrastructure and governed cloud environment required for AI/ML operations. 
• Create, maintain, and improve documentation for methodologies, code, assumptions, experiments, evaluation artifacts, and decisions, including documentation of AI tools within the software bill of materials (SBOM), 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. 

Required qualifications 

• 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, problem-solving, and critical-thinking 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 candidates to either be U.S. citizens or pass clearance through the Foreign National Government System which will require that candidates have lived within the United States for at least 3 out of the previous 5 years, have a valid and non-expired passport from their country of birth and appropriate 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. 

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–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.

Benefits: 

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. 

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