Job Description

Role Description

We are seeking a Data Scientist that is reliable, enthusiastic, and a team player. This role involves working closely with stakeholders, data engineers, analysts, and domain experts to develop transparent, explainable, and defensible analytical solutions in a regulated environment. The ideal candidate has strong analytical skills, experience working with complex datasets, and the ability to clearly communicate insights and recommendations to both technical and non-technical audiences.

Qualifications

• 5+ years of professional experience performing data science or advanced analytics work
• Strong proficiency in Python or R and SQL
• Experience applying statistical methods and machine learning techniques (e.g., regression, classification, clustering, time series)
• Experience working with large, complex, or structured datasets
• Ability to clearly communicate analytical findings to non-technical stakeholders
• Ability to work independently and collaboratively in a remote environment
• Familiarity with working in regulated or compliance-driven environments
• Experience with data visualization and BI tools (e.g., Power BI, Tableau)
• Experience supporting use cases such as fraud detection, risk analysis, program integrity, performance measurement, or policy analysis
• Understanding of data governance, privacy, and responsible AI concepts
• Certifications (a plus): cloud analytics certifications, data science certifications, or related credentials

Requirements

• Languages: Python, R, SQL
• Libraries/Frameworks: pandas, NumPy, scikit-learn, statsmodels, TensorFlow/PyTorch
• Visualization: Power BI, Tableau, matplotlib, seaborn
• Platforms: Cloud or hybrid analytics environments such as AWS, Azure, GCP
• Collaboration: Microsoft Teams, SharePoint, Jira, Confluence

Responsibilities

• Apply statistical analysis, data mining, and machine learning techniques to address operational needs
• Develop, validate, and deploy predictive, descriptive, and diagnostic models in support of program objectives
• Perform exploratory data analysis (EDA) to identify trends, patterns, anomalies, and risk indicators
• Collaborate with data engineering teams to define data requirements, feature engineering approaches, and analytic pipelines
• Ensure analytical methods and outputs are explainable, reproducible, and auditable
• Develop and document model assumptions, methodologies, limitations, and performance metrics
• Support use cases such as forecasting, risk scoring, anomaly detection, classification, and segmentation
• Create visualizations, dashboards, and analytical summaries to communicate findings to stakeholders
• Support validation, testing, and continuous monitoring of models to ensure ongoing performance and compliance
• Produce high-quality documentation, technical memos, and briefings in accordance with federal standards
• Participate in Agile/Hybrid delivery processes, including sprint planning, reviews, and status reporting

Benefits

• Paid time off – 11 holidays plus vacation and sick time.
• Health & Dental Insurance, voluntary employee-paid Vision Insurance.
• 401k – Our 401k plan matches up to 3.5% of your income (SIMPLE IRA capped at 3%).

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