Healthcare Data Scientist

Pharmaceutical Strategies Group (PSG) is a leader in pharmacy intelligence, dedicated to developing innovative drug management solutions. The Healthcare Data Scientist will enhance the Artemetrx platform by utilizing healthcare data to improve client decision-making and support AI-enabled drug management tools.

Responsibilities:

• Support the development and maintenance of predictive, statistical, and machine learning models that address business and client needs across Artemetrx initiatives
• Analyze pharmacy and medical claims data as well as other healthcare data sets to identify trends, patterns, outliers, and opportunities that inform client strategy and improve health outcomes
• Assist with AI roadmap initiatives
• Prepare, clean, transform, and validate data sets to ensure accuracy, completeness, and usability for advanced analytics, reporting, dashboards, and model development
• Develop clean, reusable, and testable analytical code using established data team standards, libraries, and modules
• Support Artemetrx through maintenance of reference tables and other data sets used within the product
• Use programming languages such as SQL or Python to extract, manipulate, and analyze large and complex data sets
• Collaborate with consultants, clinicians, analysts, product teams, data engineers, and other stakeholders to understand business problems, define requirements, and deliver actionable insights
• Document analytical methods, assumptions, data definitions, model logic, and results to support transparency, repeatability, and quality control
• Communicate analytical findings and recommendations through written summaries, presentations, dashboards, and stakeholder discussions
• Stay current with developments in healthcare analytics, data science, machine learning, artificial intelligence, and the pharmacy benefits management industry

Requirements:

• At least 2+ years of healthcare and/or pharmaceutical analytics experience
• Strong experience using SQL to write queries
• Python or R experience, in particular experience building data analysis, machine learning, or forecasting models
• 2+ years of experience in data science, analytics, statistics, healthcare analytics, informatics, or a related analytical role preferred
• Bachelor's degree in Data Science, Statistics, Mathematics, Computer Science or a related quantitative discipline required; master's degree or relevant coursework preferred
• Experience working with healthcare data, pharmacy/PBM data, medical claims, financial data, or similarly complex data sets
• Working knowledge of SQL for data extraction, querying, and data manipulation
• Proficiency with Python or R for data analysis, statistical modeling, machine learning, or automation
• Foundational understanding of statistics, predictive modeling, supervised and unsupervised learning, regression, classification, clustering, forecasting, and model evaluation techniques
• Experience preparing, cleaning, validating, and analyzing raw data with a high degree of accuracy and attention to detail
• Ability to translate business questions into analytical approaches and communicate results in a clear, concise, and practical manner
• Strong problem-solving skills, intellectual curiosity, resourcefulness, and ability to learn new tools, methods, and healthcare concepts quickly
• Strong written and verbal communication skills, with the ability to collaborate effectively with technical and non-technical stakeholders
• Demonstrated ability to work independently and as part of a cross-functional team while managing multiple priorities and deadlines
• Proficiency with Microsoft Excel, Word, Outlook, and PowerPoint. Advanced Excel skills a plus
• Ability for some travel, up to 10%
• Exposure to healthcare cost, utilization, clinical, pharmacy, PBM, or drug management analytics
• Experience with predictive modeling, time-series forecasting, claims analytics, anomaly detection, natural language processing, or AI-enabled reporting
• Familiarity with data privacy, data governance, HIPAA considerations, and secure handling of sensitive healthcare information
• Experience supporting dashboards, reporting automation, reusable analytical workflows, or model deployment processes