Data Science Analyst - Intermediate

$70,000 - $80,000/Yr

Independent Health Association

Full-time - Mid Level

10,001+ employees

About the position

The Data Science Analyst-Intermediate will analyze large datasets, develop predictive models, and perform outcomes analysis to support data-driven decision-making within the organization. This role requires a strong foundation in data analysis, a keen interest in healthcare, and the ability to leverage emerging technologies such as AI and machine learning. The analyst will stay updated with industry trends and apply new techniques as appropriate.

Responsibilities

• Collect, clean, and preprocess data from multiple sources.
• Perform exploratory data analysis (EDA) to identify trends, patterns, and anomalies.
• Independently build and deploy machine learning models, including classification and regression models.
• Assist with building and deploying complex machine learning models.
• Design and implement data visualizations to communicate complex findings clearly and concisely.
• Perform outcome evaluation of business initiatives related to cost and utilization, population assessments, and care management programs.
• Present methodology for assigned projects at methods review meetings.
• QA own work and work of others when assigned.
• Collaborate with team members on various data-driven projects.

Requirements

• Bachelor's degree in a quantitative/research discipline such as epidemiology, statistics, econometrics, behavioral economics, data sciences, or related discipline required.
• Three (3) years of analytics experience required or Master's degree plus one year of experience.
• Experience in a managed health care environment preferred.
• Experience in the application of modern statistical design and research techniques to health-related data.
• Experience working with data warehouses to extract, clean, and transform data.
• Knowledge of healthcare concepts and healthcare data, such as CPT, HCPCS, DRG, ICD-10/ICD-9 Code.
• Knowledge of data mining concepts.
• Experience in developing, training, tuning, and evaluating machine learning models.
• Knowledge of software for statistical analysis and data mining: SQL, SAS, R, Python.
• Ability to work with minimal supervision on major projects.
• Excellent problem-solving, interpersonal, analytical, and critical thinking skills.

Nice-to-haves

• Experience in healthcare analytics.
• Familiarity with emerging technologies in data science and machine learning.

Benefits

• Scorecard incentive eligibility
• Full range of benefits
• Generous paid time off