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CareFirst BlueCross BlueShield · 7 hours ago

Data Scientist- Value-Based Care Reporting (Hybrid)

Baltimore, MD

Full-time

Hybrid

Mid Level

$86K/yr - $172K/yr

3+ years exp

CareFirst BlueCross BlueShield is seeking an experienced Data Scientist specializing in Value-Based Care Reporting. The role involves using advanced analytical techniques to solve business problems and support data science initiatives while collaborating with various teams and educating on AI and machine learning.

Health CareNon ProfitService Industry

No H1B

Responsibilities

Mines and extracts data and applies algorithms to derive insights

Contribute to the analytics, reporting and data governance activity related to Attribution/Roster Management, Grouper and Data Validation, Budget/Target Reporting, Quality/Risk Coding Integration and Cost of Care/Opportunity reporting

Support items like AI implementations, partnerships with our IT/Data Management teams, vendor support (ex: Milliman MedInsight) and other related functions

Explores data to understand the data profile and its limitations

Assists business units in the innovation of organizational performance

Explores data patterns using existing data science tools

Translates business priorities to data science deliverables

Reviews trends in the ML/AI/DS space and assists with integrating new ML/AI designs into solutions and products

Qualification

Statistical modelingMachine learningData miningHealthcare analyticsData science toolsCommunication skillsIndependent workTeam mentoring

Required

Bachelor's Degree in Statistics, Mathematics, Computer Science or related field OR in lieu of a Bachelor's degree, an additional 4 years of relevant work experience is required in addition to the required work experience

3 years of relevant work experience

Ability to work independently without detailed guidance

Ability to communicate effectively and document objectives and procedures

Ability to leverage a variety of data science tools and frameworks

Knowledge in model evaluation, tuning and performance, operationalization, and scalability of scientific techniques

Knowledge of software engineering principles and practices

Proficiency in statistical modeling applications