À propos
AI Data Scientist . This exciting opportunity focuses on leveraging applied machine learning to enhance our existing production AI and analytics platform within the healthcare sector. Contribute innovative ideas and prototypes across our AI and machine learning portfolio. The ideal candidate will have hands-on experience with healthcare data, strong fundamentals in machine learning and statistics, and the ability to convert insights into impactful dashboards. Responsibilities In this role, you will support: Production AI & Prototyping:
Enhance and expand our existing AI/analytics platforms while developing new applications to address complex public sector healthcare challenges through research and rapid prototyping. Model Development & Interpretability:
Build interpretable and defensible ML models to support user workflows, including explainable feature attribution and structured model output summaries. Client Deliverables & Communication:
Create high-quality reports and presentations that effectively convey methods, findings, limitations, and recommended actions to non-technical audiences. Governed GenAI & LLMs:
Design solutions that include prompt engineering and workflow automation with rigorous evaluation and compliance for regulated use. Operational ML Excellence:
Monitor model performance by defining acceptance metrics and data health, and create dashboards for tracking KPIs. Business Development Support:
Assist in proposals by drafting technical sections, solution diagrams, and participating in capability demonstrations. Cross-Functional Collaboration:
Work with domain experts to translate requirements into quantitative solutions and validate outcomes. Engineering Best Practices:
Collaborate with data engineering teams to develop scalable pipelines with robust quality controls and documentation. Qualifications Consulting-Grade Communication:
Ability to produce clear, client-ready reports and presentations. Applied ML & Statistical Rigor:
Strong skills in applied ML on large-scale data with a focus on interpretability and defensible anomaly scoring. End-to-End ML Delivery:
Proven experience from problem framing to deployment in operational workflows. Healthcare Data Expertise:
Familiarity with healthcare data, including feature engineering and validation for audits. Applied Generative AI:
Experience with prompt design and API integration for governed retrieval. Production Engineering:
Proficiency in Python, OOP, and modern engineering practices, including Git/GitHub. Data at Scale:
Proficiency in SQL and distributed processing technologies, focusing on data quality and validation. Required: Bachelor's degree in Data Science, Computer Science, Statistics, or related field. 5+ years of experience in data science or ML roles. Preferred: Master's degree in relevant fields. Experience facilitating client workshops to define scope and success metrics. Ability to translate model outputs into structured, explainable artifacts for stakeholders. Experience leading executive briefings and aligning stakeholders on findings. Familiarity with MLOps and DevOps practices. Experience with time series analysis and graph analytics. Cloud-based data platforms capabilities. Experience in building document ingestion pipelines. Location This role requires 2 to 3 days per week of on-site work at our Indianapolis office. Compensation The salary range for this position is $93,700 - $154,500, along with performance-based bonuses and a comprehensive benefits package. The Indianapolis Health Practice has 250+ full-time employees from diverse backgrounds and works cross-functionally with a range of specialists. Join us for a chance to work on challenging problems and contribute meaningfully to our client programs. Equal Opportunity All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, national origin, disability, or protected veteran status.
Compétences linguistiques
- English
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