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LivantaLLC logo
LivantaLLC

Advancing healthcare quality through innovation

Data Scientist

Data ScientistData ScientistFull TimeRemoteSeniorTeam 201-500Since 2004H1B No SponsorCompany SiteLinkedIn

Location

United States

Posted

50 days ago

Salary

$115K - $150K / year

Seniority

Senior

Job Description

Data Scientist

LivantaLLC

• The Data Scientist combines advanced analytics and machine learning with deep domain knowledge to generate clinical and operational insights, build predictive models, and support decision-making across the healthcare ecosystem. • 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.

Job 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.

Benefits

  • Health insurance
  • Retirement plans
  • Paid time off
  • Flexible work arrangements
  • Professional development

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