People and Project Leadership

• Manage the ML Ops team, help ML Ops engineers take ownership and deliver best outcomes, focusing on quality and productivity

• Will be responsible for supervising, managing, and motivating team members on a day-to-day basis
• Create a framework for communication, project management and execution across team to help drive best practises
• Work under the guidance of DS director, implement policies and procedures that will improve operations
• Collaborate closely with stakeholders to understand key result areas, ensure expansion and penetration of data science use-cases
• Develop a pipeline of ML Engineering talent and leadership, and contribute to an inclusive community of data analytics practitioners/ thought leaders

• Be able to act proactively to ensure smooth team operations and effective collaboration

Strategic growth and thought leadership

• Strategize on key opportunities/ whitespaces, drive discussions and expand outcomes from LCCI for data science solutions
• Focus on the future business needs and expand capabilities of the group
• Integrate working model for analytics capabilities across BI&A teams, and where possible, across other LCCI teams to drive better cross-team resourcing, cross-pollination of best practices.
• Conducting quarterly/ annual performance reviews of the team and motivate team to achieve excellent results
• Go beyond to support BI&A leadership to implement out of box solutions which support Lilly’s organizational objectives.

Required Skills and Expertise:

• 12+ years of relevant experience in an ML Ops or Dev Ops space
• At-least 6+ years’ experience in leading highly competent and analytics-oriented teams
• Persuasive communication and inter-personal skills
• High level of motivation and a strong desire to find creative solutions to challenging situations.
• Demonstrated ability to enforce business rules and policies in a constructive but disciplined manner
• Substantial analytics experience and understanding of complexities in specialty markets, analytics techniques, and US pharmaceutical business
• Proven ability to manage resources to achieve project and business results

Education

• Bachelor’s/ Master’s degree in Computer Applications/ Mathematics/ Pharma or a related field from a premium college