Associate Director - Machine Learning Operations

Key Responsibilities:

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 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 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 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