Opportunity Details

The AI Product Manager position entails spearheading the definition and delivery of AI solutions in a Healthcare payer environment. This role leverages a blend of extensive Data and AI expertise and practical experience to generate business value aligned with the AI product vision and company objectives.

Key Responsibilities:

  • Lead the development roadmap for AI Products within the designated domain.
  • Oversee stakeholder engagement and value delivery through AI Products.
  • Manage the entire AI Product development lifecycle, from use case intake to production delivery.
  • Collaborate with a highly skilled team of AI/ML Engineers, Business Systems Analysts, Data Product Managers, and Business Partners.
  • Gain a deep understanding of company business strategies and goals, identifying opportunities to effectively utilize AI for enhancing business outcomes.
  • Utilize market insights to identify and develop AI product opportunities by leveraging Applied AI, data engineering, data warehousing, and data visualization.
  • Collaborate with business partners to prioritize AI Product feature development, aligning business and technical objectives.
  • Translate business requirements into detailed product requirements.
  • Manage complex product and technical decisions, ensuring development progresses through an agile methodology.
  • Monitor and communicate the success of AI products, conducting analysis to enhance accuracy and effectiveness.

Qualifications and Requirements:

  • Prefer an academic degree in Data Science, Computer Science, Statistics, or a related field.
  • Healthcare Payer knowledge is a plus but not required.
  • Strong capabilities in requirement analysis and solution design, working with cross-functional teams to align objectives and develop technical plans.
  • Expertise in data preprocessing and feature engineering to extract insights from raw data while adhering to data and AI principles.
  • Experience in model prototyping and development, collaborating with engineers and stakeholders to deliver models using best practices.
  • Proficiency in experimentation and evaluation of AI models, including metric development and selection.
  • Ability to deploy and optimize models for real-time performance in collaboration with ML Engineers.
  • Familiarity with machine learning frameworks and libraries (e.g., TensorFlow, PyTorch, scikit-learn).
  • Knowledge of NLP (Natural Language Processing) is a plus, with expertise in libraries like NLTK, spaCy, or Hugging Face transformers.
  • Experience with model development and evaluation, including a strong foundation in model evaluation and metric selection.
  • Understanding of production systems and software engineering principles for deploying ML models.
  • Proficiency in data preprocessing and analysis, including SQL and Python data processing libraries.
  • Experience with SQL for analysis, analytics, and transformation, as well as familiarity with RDBMS.
  • Understanding of Cloud Data Warehouses, such as Snowflake, and related concepts like master data management and system integrations.

Additional Qualities:

  • Ability to influence and make analytical insights relevant for driving high-quality decisions.
  • Excellent communication and presentation skills at all organizational levels.
  • Experience with data instrumentation, data ingestion, data enrichment, and data syndication in a cloud-based environment.
  • Demonstrated expertise in AI product development and project management.
  • Skill in facilitating cross-functional planning sessions, such as Scrum and Squad in agile.
  • Strong partnership, collaboration, and inspiration skills, including remote team management.
  • Effective negotiation and issue resolution capabilities.
  • A foundation in mathematical concepts underlying machine learning, deep learning, NLP, statistical modeling, and data analysis.
  • Familiarity with production systems and MLOps (Machine Learning Operations).

Download Part 2:
Initiation, Strategic Vision & CX - HCD