Data Scientist I

Job Title: Data Scientist l Position Summary: A Data Scientist l will be responsible for leveraging data to provide actionable insights, drive decision-making, and optimize healthcare and business outcomes. Th role will use their strong background in data science, a passion for healthcare, and the ability to work in a cross-functional environment with product owners, data engineers, and business stakeholders. Key Duties and Responsibilities: Participate in all project phases from concept, requirements, development, test, and production support Explore and understand new big data and analytic technologies that enable faster and more efficient system operations, ultimately delivering timely insights and models. Ensure the security, confidentiality, and integrity of client information Data Analysis & Modeling: Create and refine predictive algorithms that support the suite of Star Quality product offerings as well as the overall client satisfaction initiatives for Pareto IntelligenceTM. Analyze large and complex healthcare datasets (e.g., clinical, operational, and patient data) to identify trends, patterns, and insights. Develop predictive models and advanced analytics to inform healthcare strategies and program decisions. Machine Learning & AI: Design, develop, and deploy machine learning algorithms and artificial intelligence solutions to improve insights, workflows, predictive diagnostics, outcomes, and operational efficiency. Explore and understand new big data and analytic technologies that enable faster and more efficient system operations, ultimately delivering timely insights and models. Data Integration & Cleaning: Work with diverse healthcare data sources, including electronic health records (EHR), claims data, clinical trial data, and sensor data, ensuring data is clean, accurate, and well-prepared for analysis. Collaboration with Cross-Functional Teams Collaborate closely with healthcare professionals, product teams, engineers, and business stakeholders to define analytical goals, communicate insights, and implement data-driven solutions. Participate in all project phases from concept, requirements, development, test, and production support Visualization & Reporting: Create clear, actionable reports and dashboards that communicate complex data findings to non-technical stakeholders, including clinicians, executives, and healthcare administrators. Continuous Improvement: Stay up-to-date with the latest advancements in data science, healthcare technology, and analytics tools. Contribute to the development of new methodologies and approaches for improving Star analytic capabilities and supporting client needs through data science. Compliance & Security: Ensure all data analyses and machine learning models maintain the integrity of client information and comply with healthcare regulations such as HIPAA, data privacy laws, and security best practices. Education and Experience: Master’s degree or Ph.D. in Data Science, Computer Science, Statistics, Epidemiology, Biomedical Engineering, or a related field. Experience: 3+ years of experience in data science, with a focus on healthcare or life sciences (or equivalent academic/research experience). Strong experience with machine learning algorithms, statistical modeling, and data analytics tools. Familiarity with healthcare data sources and formats, including EHR/EMR systems, claims data, HEDIS data, survey-based data and prescription drug event data. Technical Skills: Proficiency in programming languages such as Python, R, or SQL. Experience working in JupyterHub environment and experience with data manipulation libraries (e.g., Pandas, NumPy,), machine learning frameworks (e.g., scikit-learn, TensorFlow, PyTorch), and statistical analysis tools. Knowledge of data visualization tools such as Tableau, Power BI, or custom dashboards. Familiarity with cloud computing platforms (AWS, Google Cloud, Azure) is a plus. Analytical & Problem-Solving Skills: Strong ability to work with design experiments, and develop complex models to solve healthcare-related challenges. Experience/exposure to big data technologies such as Hadoop, Spark, Docker, and Airflow preferred. Communication Skills: Ability to present complex data and technical findings in a clear, concise, and actionable manner to both technical and non-technical audiences. Healthcare Knowledge: A solid understanding of healthcare systems, clinical workflows, and healthcare industry regulations (HIPAA, HITRUST, etc.) is a plus. Preferred Qualifications Experience working with Medicare Advantage, Star Ratings, clinical decision support tools, healthcare prediction models, or patient outcome tracking systems. Familiarity with Natural Language Processing (NLP) and text mining techniques for processing unstructured healthcare data. Experience with healthcare reimbursement and claims data analysis. Knowledge of health economics, epidemiology, or health policy. Knowledge, Skills, and Abilities: Complex Problem Solving - Ability to identify and solve problems by reviewing related information, evaluating options and implementing solutions. Critical Thinking - Ability to use logic and reason to identify strengths and weaknesses of alternative solutions, conclusions, or approaches to problems. Deductive Reasoning – Ability to apply general rules to specific problems to produce answers that make sense. Inductive Reasoning – Ability to combine pieces of information to form general rules or conclusions (includes finding a relationship among seemingly unrelated information or events). Quantitative and Analytical Skills - Ability to apply quantitative and statistical analysis techniques to unstructured problems. Strong Communication Skills – Ability to communicate information and ideas orally and in writing clearly and concisely. Positive, flexible, and self-motivated attitude, along with the ability to work as a collaborative team player. Excellent attention to details, accuracy and follow up. Ability to set priorities and work on multiple tasks simultaneously. Excellent oral and written communication skills.