AI Developer - C1 Gov
C1
ApacheAWSAzureCloudCyber SecurityDockerHadoopJavaKubernetesPythonPyTorchScikit-Learn+4 more
Data Scientist – Federal Health
LivantaLLC
full-time
Posted on:
Origin: • 🇺🇸 United States • North Carolina
Visit company websiteSalary
💰 $115,000 - $165,000 per year
Job Level
Mid-LevelSenior
Tech Stack
ApacheAWSAzureCloudPythonPyTorchScikit-LearnSparkSQLTensorflow
About the role
- 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).
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