Data Scientist – Federal Health

Job not on LinkedIn

September 21

🌲 North Carolina – Remote

Although this job is listed in North Carolina, this company may be open to hiring remote in other states.

🦀 Maryland – Remote

Although this job is listed in Maryland, this company may be open to hiring remote in other states.

+1 more states

🌲 North Carolina – Remote 🦀 Maryland – Remote ⚔️ Virginia – Remote

💵 $115k - $165k / year

⏰ Full Time

🟡 Mid-level

🟠 Senior

📊 Data Scientist

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LivantaLLC

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Healthcare Insurance • Education • Data Management

Livanta LLC is a technology-enabled organization dedicated to advancing healthcare quality through innovation. It specializes in providing services to patients, caregivers, healthcare providers, and payers, focusing on improving health outcomes, navigating healthcare systems, and ensuring payment accuracy. Livanta is recognized as the largest Medicare Quality Improvement Organization and offers a range of services including quality oversight, auditing, advocacy, and data analytics to enhance patient care and safety while managing healthcare costs effectively.

201 - 500 employees

Founded 2004

⚕️ Healthcare Insurance

📚 Education

📋 Description

• Prepare and analyze large and complex datasets to identify trends, patterns, and insights that drive business decisions. • Develop, implement, and optimize machine learning models, including Generative AI, for predictive analytics, classification, and other applications. • Apply statistical techniques to analyze data and build models that forecast future trends and behaviors (e.g., risk stratification, disease progression, readmission likelihood). • Create compelling data visualizations and dashboards to effectively communicate findings and insights to stakeholders. • Connect and match within and across data sources both internal/ external to augment and enhance analyses. • Work closely with cross-functional teams, including data engineers, software developers, and business analysts, to gather requirements and deliver data solutions. • Stay current with industry trends and advancements in data science and integrate new techniques and tools into existing workflows. • Identify, review, and execute impactful analytical approaches from industry whitepapers. • Translate complex data into actionable insights to support clinical decision-making, care optimization, and operational efficiency, often through dashboards or reports. • Collaborate with clinicians, informaticists, and SMEs to derive relevant features from health data, such as comorbidity indices, lab value trajectories, or time-to-treatment measures. • Ensure data use complies with HIPAA, 42 CFR Part 2, and other applicable regulations. • Apply de-identification, data masking, or differential privacy techniques when needed. • Help define and sometimes implement workflows for data acquisition, preprocessing, and model inference pipelines, often in cloud-based environments (e.g., AWS, Azure). • Identify and mitigate potential biases in data or models, and ensure outputs are interpretable by clinical or policy stakeholders. • Monitor model performance over time and retrain or recalibrate as necessary to maintain accuracy and relevance in evolving clinical environments.

🎯 Requirements

• Bachelor’s degree in Data Science, Computer Science, Statistics, Mathematics, or a related field; Master’s or PhD preferred. • Minimum of 4 years of experience in data science or a related field. • Proficiency in programming languages such as Python, R, or SQL. • Demonstrated experience practically leveraging and deploying AI/ML models to production. • Working knowledge of Generative AI tuning and implementation techniques and toolsets i.e. AWS Bedrock, LangChain, Anthropic MCP, and LlamaIndex. • Experience with big data frameworks/ toolsets such as Apache Spark, Databricks, and AWS EMR Studio. • Experience with AI/ machine learning libraries and frameworks (e.g., TensorFlow, Scikit-Learn, PyTorch, and Spark ML Flow). • Experience working with healthcare datasets such as EHRs, medical claims, FHIR, HL7, or patient-reported outcomes. • Familiarity with healthcare regulations and standards (e.g., HIPAA, 42 CFR Part 2, HEDIS, CMS measures). • Demonstrated experience working with Notebook tools such as Databricks/ Jupyter. • Strong understanding of statistical analysis and modeling techniques. • Experience with data visualization tools (e.g., Amazon Quicksight, Power BI, Matplotlib). • Excellent problem-solving skills and attention to detail. • Strong communication and interpersonal skills, with the ability to work effectively with diverse teams and stakeholders. • AI/ ML certifications (preferred). • Familiarity with Databricks, Snowflake, or other modern data platforms (preferred). • Understanding of data governance and security frameworks relevant to healthcare (e.g., NIST, HITRUST) (preferred). • Prior experience working with government agencies (e.g., CMS, VA, DoD) or payer/provider organizations (preferred). • Knowledge of healthcare delivery systems and policy frameworks (preferred).