Job Overview: Senior Data Scientist will have a strong background in statistical analysis, machine learning, and data modeling. The Data Scientist will play a key role in extracting valuable insights from our data, contributing to policy decision-making processes, and developing innovative solutions to complex problems. Primary Responsibilities Include (but not limited to): Data Analysis and Interpretation: • Conduct exploratory data analysis to discover trends, patterns, and anomalies. • Develop and implement statistical models for predictive and prescriptive analysis. • Interpret and communicate data-driven insights to non-technical stakeholders. Data Preparation and Cleaning: • Clean and preprocess raw data to ensure accuracy and reliability. • Work with large datasets from diverse sources and formats. • Collaborate with data engineers to create and maintain data pipelines. Algorithm Development: • Develop algorithms for solving complex business problems. • Implement algorithms for pattern recognition, clustering, and classification. Collaboration and Communication: • Collaborate with business analysts, data engineers, and other stakeholders to understand business requirements. • Present findings and insights in a clear and understandable manner to both technical and non-technical audiences. Required Qualifications: • Bachelor's degree in a quantitative field (e.g., Computer Science, Statistics, Mathematics, Physics), master's degree in IT field, or equivalent experience in Data Science. • Proven experience as a Data Scientist or similar role. • Fluent in Structured Query Language (SQL) • Experience with Tableau and Power BI • Proficiency in statistical analysis and data visualization tools. • Excellent problem-solving and critical-thinking skills. • Strong communication and collaboration skills. Preferred Qualifications: • 5+ years working in an Analytics position for a large-scale IT system. • Working knowledge of Healthcare Programs (i.e., Medicaid). • An understanding of healthcare enterprise systems (including, but not limited to claims, finance, members, providers), with the ability to understand and communicate from a business and technical perspective. • Knowledge of big data technologies and tools. • Holding industry recognized data science certifications, for example: • Certified Analytics Professional (CAP) • IBM Data Science Professional Certificate • Microsoft Certified: Azure Data Scientist Associate • SAS Certified AI and Machine Learning Professional • SAS Certified Data Scientist Experience with tools like ArcGIS, Toad, SAS, SPSS, and RStudio.