Full-Time

Manager - Data Science

Deadline 2/11/27
IEHP

IEHP

Compensation Overview

$154.1k - $204.2k/yr

Rancho Cucamonga, CA, USA

Hybrid

Hybrid schedule: remote Mon & Fri; on-site Tue-Thu in Rancho Cucamonga, CA.

Category
Data & Analytics (1)
Required Skills
LLM
Kubernetes
MLOps
Microsoft Azure
Python
JavaScript
Data Science
Tensorflow
R
Pytorch
SQL
Machine Learning
Java
MLflow
RAG
LangChain
Data Governance
Requirements
  • At least ten years of experience, including a minimum of seven years of experience in data science and machine learning and at least five years in a leadership/managerial role.
  • Proven track record in leading AI/ML projects from conception to production.
  • Experience with cloud AI platforms (Azure Machine Learning, Google Cloud Vertex AI) and/or on-prem MLOps setups.
  • Direct experience in Managed Care and Healthcare analytics, including claims data, care management, utilization, risk adjustment, member engagement, or related areas.
  • Exposure to multimodal AI (text, image, audio, video) applications.
  • Experience with Kubernetes, KServe, Ray, or MLflow for scaling AI workloads.
  • Bachelor's Degree in Mathematics, Statistics, Computer Science, or related field from an accredited institution.
  • Master's Degree in Mathematics, Statistics, Computer Science, or related field from an accredited institution is preferred.
  • Familiarity with basic principles of distributed computing and/or distributed databases.
  • Knowledge of one or more business/functional areas. Working knowledge of diagnosis and procedure coding, medical terminology, knowledge of managed care, claims payment processes, and insurance terminology.
  • Familiarity with data governance, model interpretability, bias mitigation, and AI ethics.
  • Strong analysis and critical thinking skills.
  • Excellent communication and interpersonal skills.
  • Strong programming skills in Python, PyTorch/TensorFlow, LangChain, Hugging Face, or equivalent framework.
  • Ability to manipulate large datasets and using database and general-purpose programming language (R, Python, JavaScript, or other big data frameworks, Java, SQL).
  • Demonstrable ability to quickly understand new concepts all the way down to the theorems, and to come out with original solutions to mathematical issues.
  • Ability to multi-task while maintaining careful attention to detail. Ability to handle multiple projects, data input, and strong problem-solving capability. Independent self-starter who is driven to success, takes great pride in accomplishments and works with a sense of urgency to meet deadlines and address competing priorities.
  • Expertise in Generative AI (LLMs, transformers, embeddings, vector databases, RAG, fine-tuning, and prompt engineering). Strong business acumen and ability to translate technical solutions into executive-level impact stories.
Responsibilities
  • Lead and mentor a team of data scientists, ML engineers, and AI specialists.
  • Define and execute the roadmap for AI/ML and Generative AI initiatives across the enterprise.
  • Partner with business and technology stakeholders to identify AI use cases that create measurable value.
  • Advocate for responsible AI practices, ensuring solutions are ethical, explainable, secure, and compliant.
  • Oversee development of advanced ML models and AI systems (predictive, prescriptive, and generative).
  • Design and implement GenAI solutions, including LLM fine-tuning, embeddings, retrieval-augmented generation (RAG), and prompt optimization.
  • Drive end-to-end MLOps practices: model training, evaluation, deployment, monitoring, and lifecycle management.
  • Ensure scalability and performance of AI solutions within enterprise data platforms.
  • Collaborate with data engineering to optimize data pipelines for AI workloads.
  • Stay at the forefront of GenAI, multimodal AI, and emerging ML techniques to evaluate their relevance and application.
  • Foster a culture of experimentation, rapid prototyping, and “fail-fast and pivot” approaches.
  • Hire, train, and manage support staff, while monitoring and evaluating outcomes. Conduct performance reviews of each team member within IEHP guidelines.
  • Perform any other duties as required to ensure Health Plan operations and department business needs are successful.

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