Job description

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. Purpose and Scope: We are seeking a Data Scientist to join our Data & AI team. This role will apply advanced analytics, machine learning, and artificial intelligence to large and complex datasets to identify patterns, develop predictive insights, and support high-impact decision making. The ideal candidate is a hands-on data scientist who is comfortable working directly with stakeholders, developing analytical approaches from ambiguous problems, and communicating complex findings clearly. This position is contingent upon contract award. Responsibilities: • Design, develop, test, and maintain advanced statistical, machine learning, and AI models. • Develop supervised and unsupervised models including regression, classification, clustering, anomaly detection, and related approaches. • Analyze large structured and unstructured datasets using Python, Pandas, and SQL. • Support development and implementation of semantic layer architectures. • Develop analytical methods, indicators, and models to identify patterns, anomalies, relationships, and potential risk. • Work directly with investigative and business stakeholders to translate questions into analytical approaches and actionable findings. • Develop and scale natural language processing solutions, including techniques such as semantic analysis, OCR, and large language models. • Develop dashboards, visualizations, and analytical products to communicate methods, findings, and recommendations. • Document analytical methodologies, model testing, assumptions, and results. • Collaborate with data engineers and technical teams to support analytics and machine learning in cloud environments. Competencies: • Applied Data Science : Translates complex business or investigative questions into practical analytical approaches and models. • Technical Depth : Demonstrates strong hands-on capability across Python, SQL, statistical modeling, machine learning, and modern AI techniques. • Problem Solving: Works effectively with incomplete or complex data and adapts analytical approaches as requirements evolve. • Communication: Clearly explains analytical methods and findings to technical and non-technical stakeholders. • Collaboration: Works effectively with stakeholders, data engineers, and other technical team members to deliver usable analytical solutions. Requirements • U.S. citizenship is required for this position due to federal government contract requirements. • Ability to obtain & maintain a Public Trust clearance. • Master’s degree, Ph.D., or equivalent advanced degree in Data Science, Machine Learning, Computer Science, Mathematics, or a related field. • 10+ years of applied experience in Data Science, Machine Learning, Computer Science, Mathematics, or a related field. • Hands-on experience developing advanced AI, machine learning, predictive, and statistical models, including supervised and unsupervised approaches. • Hands-on Python experience, including Pandas. • Hands-on experience supporting semantic layer development or implementation. • Experience working in a modern cloud environment such as Azure, AWS, or GCP. • SQL experience, including SQL Server and PostgreSQL. • Experience developing and scaling natural language processing solutions. • Experience presenting analytical methods and findings to technical and non-technical stakeholders through written products, presentations, dashboards, or visualizations. • Excellent command of written and spoken English. Desired Qualifications : • Ph.D. in Computer Science, Data Science, Machine Learning, Mathematics, or a related discipline. • Experience leading data architecture efforts to support machine learning implementations. • Experience supporting fraud, waste, abuse, financial-crime, or program-integrity analytics. • Experience with Microsoft Azure, including Azure Machine Learning, Synapse Analytics, AI Foundry, or AI Search. • Experience developing fraud indicators, risk-scoring approaches, anomaly-detection models, or investigative leads. • Experience with OCR, semantic similarity, entity resolution, or analysis of large unstructured datasets. • Experience integrating LLMs or retrieval-augmented generation solutions with enterprise data. • Experience developing analytical dashboards or network/link visualizations. • Cloud, AI, or machine learning certifications. Working Environment : eSimplicity supports a remote work environment operating within the Eastern time zone so we can work with and respond to our government clients. Expected hours are 9:00 AM to 5:00 PM Eastern unless otherwise directed by manager. Occasional travel for training and project meetings. It is estimated to be less than 5% per year. 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.

Requirements

Must-haves

This position is contingent upon contract award.
Design, develop, test, and maintain advanced statistical, machine learning, and AI models.
Develop supervised and unsupervised models including regression, classification, clustering, anomaly detection, and related approaches.
Analyze large structured and unstructured datasets using Python, Pandas, and SQL.
Support development and implementation of semantic layer architectures.
Develop analytical methods, indicators, and models to identify patterns, anomalies, relationships, and potential risk.
Work directly with investigative and business stakeholders to translate questions into analytical approaches and actionable findings.
Develop and scale natural language processing solutions, including techniques such as semantic analysis, OCR, and large language models.
Develop dashboards, visualizations, and analytical products to communicate methods, findings, and recommendations.
Document analytical methodologies, model testing, assumptions, and results.
Collaborate with data engineers and technical teams to support analytics and machine learning in cloud environments.
Applied Data Science : Translates complex business or investigative questions into practical analytical approaches and models.
Technical Depth : Demonstrates strong hands-on capability across Python, SQL, statistical modeling, machine learning, and modern AI techniques.
Problem Solving: Works effectively with incomplete or complex data and adapts analytical approaches as requirements evolve.
Communication: Clearly explains analytical methods and findings to technical and non-technical stakeholders.

Nice-to-haves

Ph.D. in Computer Science, Data Science, Machine Learning, Mathematics, or a related discipline.
Experience leading data architecture efforts to support machine learning implementations.
Experience supporting fraud, waste, abuse, financial-crime, or program-integrity analytics.
Experience with Microsoft Azure, including Azure Machine Learning, Synapse Analytics, AI Foundry, or AI Search.
Experience developing fraud indicators, risk-scoring approaches, anomaly-detection models, or investigative leads.
Experience with OCR, semantic similarity, entity resolution, or analysis of large unstructured datasets.
Experience integrating LLMs or retrieval-augmented generation solutions with enterprise data.
Experience developing analytical dashboards or network/link visualizations.
Cloud, AI, or machine learning certifications.

Application prep

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Keywords to mirror

aimachine learningpythonsqlazureawsgcp

Platform: paylocity
Effort: medium

Benefits

Benefits detected in the listing.

Dental

Vision

401(K)

Paid Time Off

Wellness