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.
- 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.
- 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).