The company is looking to establish a center of excellence for AI and ML by setting and driving an enterprise-wide data science vision. This involves transforming the data science team, shaping strategic roadmaps, influencing executive decisions, and aligning initiatives with business goals to deliver impactful AI solutions.
Requirements
- Experience using statistical computer languages (R, Python, SQL, etc.) to manipulate data and draw insights from large data sets.
- Knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and their real-world advantages/drawbacks.
- Knowledge of advanced statistical techniques and concepts (regression, properties of distributions, statistical tests and proper usage, etc.) and experience with applications.
- Fluent in complex algorithms and analytics methodologies across multiple platforms and languages.
- Experience using medical data to derive actionable business insights preferred.
- Stay current with emerging technology trends and represent the organization in external forums, conferences, and industry groups.
- Institute quality control and ethical guidelines for algorithms, code, and outputs.
Responsibilities
- Architect and oversee technical strategy for all data science initiatives, championing innovation in AI/ML methodologies and platforms.
- Lead the design, development, and deployment of ML models, focusing on advanced techniques such as Natural Language Processing (NLP), generative AI, and automation.
- Own the development and governance of a modern data platform for all data consumers.
- Lead LLM integration projects to automate manual processes and improve operational efficiency.
- Drive AI solutions for automation, decision intelligence, and enhanced customer experience.
- Translate complex data insights into actionable business strategies and measurable outcomes.
- Conduct and cross-train team to conduct comprehensive code reviews to ensure quality, maintainability, and adherence to enterprise standards.
Other
- Set and drive the enterprise-wide data science vision, ensuring alignment with executive leadership and long-term business objectives.
- Collaborate with senior leaders across IT, Product, Operations, Marketing, and other business units to identify and execute high-impact, cross-functional data initiatives.
- Manage larger, multi-disciplinary teams, mentoring and developing future leaders within the data science organization.
- Provide vision, coaching, and guidance on project prioritization, resource allocation, and career development, with a focus on succession planning and scaling teams.
- Foster a culture of innovation, continuous learning, knowledge sharing, and data-driven decision-making across the enterprise.
