business insights and analytics - sr data scientist

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 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.

Business Insights and Analytics: Data Scientist

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.

The LCCI (Lilly Capability Center India), BI&A (Business Insights & Analytics) team was started in 2017 with the objective of supporting business decisions for the commercial and marketing functions in the US and ex-US affiliates. This team is part of the LCCI - Commercial Services organization and works very closely with business analytics team based in Indianapolis (HQ). The team currently comprises of more than 100 staff members, with varied backgrounds and skills across data management, analytics and data sciences, business and commercial operations etc.

To better meet the evolving analytics needs, the LCCI BI&A team is ramping up the data sciences pillar. We are looking for a data scientist who can be a key contributor to DS-projects, provide statistical analysis with the objective of driving KPIs for the business.

Core Responsibilities

• Use advanced analytics techniques and build models to answer business questions at the intersection of the pharmaceutical and marketing spaces to provide value to commercial teams
• Dive deep into a variety of data sources to find patterns, explain trends and tie them to business outcomes
• Exhibit deep expertise on statistical/AI/ML techniques combined with strong knowledge of the commercial pharma business and the problems that are being solved by data and analytics
• Effectively work and communicate with global teams and stakeholders to present the final outcomes and provide recommendations as needed
• Stay current with respect to ML modelling methodologies, to maintain proficiency in applying new and varied methods, and to be competent in justifying methods selected
• Continuous learning and experimenting new with possibilities for consumer marketing analytics
• Collaborate with cross functional teams and external consultants to help review or translate this work to other team members
  
  
  

Experience Required

• 3-8 years of in-depth hands-on experience in building models using big data and ML/AI modelling techniques
• Extensive experience working on the following areas of machine learning and artificial intelligence: features engineering, supervised and unsupervised learning, reinforcement learning, natural language processing, deep Learning, GenAI, optimization models.
• Understanding of MLOps practices and big-data engineering, including model versioning, continuous integration and deployment pipelines.
• Prior experience on MMM is preferred
• Significant coding experience in Python and proficiency with virtual environments and containers.
• Familiarity with version control system and platform (Git and GitHub).
• Knowledge of Agile SCRUM methodologies.
• Demonstrated strength/understanding in statistics (preferred)
• Strong analytical and problem-solving skills to be able to structure and solve open ended business problems (pharma experience is appreciated)
• Experience working with digital data for Engineering/Healthcare/Retail/BFSI/Digital native companies
• Familiarity with cloud technology and AWS services for analytics
• Education
• Master’s/ Ph.D. degree in computer science, technology, statistics/mathematics, econometrics oroperations research.
  
  
  

Lilly is dedicated to helping individuals with disabilities to actively engage in the workforce, ensuring equal opportunities when vying for positions. If you require accommodation to submit a resume for a position at Lilly, please complete the accommodation request form (https://careers.lilly.com/us/en/workplace-accommodation) for further assistance. Please note this is for individuals to request an accommodation as part of the application process and any other correspondence will not receive a response.

Lilly does not discriminate on the basis of age, race, color, religion, gender, sexual orientation, gender identity, gender expression, national origin, protected veteran status, disability or any other legally protected status.

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