Machine Learning Operations Lead

Key Skills

Java Programming, Python Programming, SQL, AWS, Machine learning techniques, Google Cloud Platform (GCP), R Programming, MLOps tools, SAS

Job Description

At Lilly, we unite caring with discovery to make life better for people around the world. We are a global healthcare leader headquartered in Indianapolis, Indiana. Our 35,000 employees around the world work to discover and bring life-changing medicines to those who need them, improve the understanding and management of disease, and give back to our communities through philanthropy and volunteerism. We give our best effort to our work, and we put people first. We’re looking for people who are determined to make life better for people around the world.

At Lilly, we unite caring with discovery to make life better for people around the world. We are a global healthcare leader headquartered in Indianapolis, Indiana. Our 39,000 employees around the world work to discover and bring life-changing medicines to those who need them, improve the understanding and management of disease. We’re looking for people who are determined to make life better for people around the world

As Lilly strives to achieve these objectives, we have embarked on building and in-housing a state-of-the-art “recommendation engine” platform to enable more agile sales and marketing operations. This platform will

- ingest a wide variety of data sources,

- run advanced personalization models

- and integrate seamlessly with all other Lilly operations platforms

to provide recommendations on “what should we do next” to the sales and marketing teams at the individual doctor level, enabling better decision making and improving customer experience.

 Core Responsibilities:

As part of Omnichannel Data Transformation team, lead ML Ops engineers and Omni data engineers & work with various stakeholders to structure, deploy and refine Omnichannel Data Transformation work across Enhancements, Configuration and ML Ops work streams.

Provide thought leadership on data transformation across omnichannel execution teams.

Required Skills and Expertise:

• Masters or Bachelor’s Degree with 12+ years of relevant experience working with data engineering, data analytics and machine learning supporting Pharma/Lifesciences Commercial ops internally or in consulting.
• Proficiency in SQL, and at least one of R/Python/SAS
• Proficiency in AWS Cloud Platform and its services for data analytics, data engineering and Machine Learning.
• Proficiency in Machine Learning models and algorithms
• 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
• Strong track record of leading cross-functional teams to deliver and delivering complex cross functional projects with great flexibility
• Substantial analytics experience and understanding of complexities in specialty markets, analytics techniques, and US pharmaceutical business
• Proven ability to rally resources to achieve project and business results

Preferred Skills:

• Quantitative background in engineering, statistics, mathematics, sciences, finance, or an MBA
• Strong analytical skills coupled with business acumen, and an ability to think strategically in an ambiguous environment
• Broad awareness and working knowledge of data engineering and omnichannel analytics
• Demonstrated ability to influence change with senior stakeholders across Commercial and IT

Project Management and People Leadership Expectations:

• Deliver and implement a standardized framework for communication, project management and execution across capability groups and business focused teams
• Build, deliver and own a quality management framework to increase deliverable quality cross stakeholders with a range of tolerances and maturity in working with offshore centers
• Create and implement upskilling plans for LCCI team members within the affiliate team and/or across capability groups
• Serve as trusted career advisor, and work with Functional Leadership and HR to identify career opportunities for these team members, both systemically (career path development) and with individuals as needed
• Develop a pipeline of analytics talent and leadership, and contribute to an inclusive community of analytics expert practitioners
• Strategic Growth and Thought Leadership