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 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.

Position Overview
Lilly is a global healthcare leader headquartered in Indianapolis, Indiana, USA with many global locations including our LCCI site located in Bangalore, India. Our 34,000 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 are looking for people who are determined to make life better for people around the world.

The Synthetic Molecule Design and Development (SMDD) Organization within the Lilly Research Labs is an integrated synthetic molecule drug development organization which spans drug discovery and development phases from early discovery to submission and post-approval. The automation and data sciences team within SMDD is a cross-functional group of chemists, engineers, and computational chemists with a broad range of computational modeling and data science capabilities complemented by engineering and synthetic organic chemistry competencies. This group drives innovation in the drug substance development process through the efficient combination of organic synthesis expertise coupled with computational modeling, automation, data sciences, and data rich experimentation.

Identify opportunities where predictive analytics can enhance and accelerate decision-making, create and execute the plan using predictive analytics to answer the business question.
Experience in working with different data types and source systems as well as interfacing databases to enable extracting relevant data to address business questions
Experience in statistics/machine learning techniques to be able to use the right tool for the right question
Ability to communicate the results of analysis in an effective manner to stakeholders to drive action
Key Responsibilities
Work with partners across SMDD to identify decisions that can be informed by predictive analytics
Build decision support tools, templates, dashboards for high frequency decisions that can leverage analytics.
Develop tools/algorithms to mine patterns in existing data to create a recommendation on future questions to consider
Integrate predictive analytics capabilities with knowledge management
Educational Requirement
Ph.D. in a quantitative discipline (such as Statistics, Mathematics, Computer Science, Operations Research, Engineering) or M.S with 5-10 years industry experience in doing predictive analytics

Position Requirements
Experience in working with varied data types (structured and unstructured) and databases
Experience in programming in scripting languages including R and Python with exposure to other platforms as a plus (i.e., Perl)
Proficiency in Microsoft products (Excel, Access, Word, Power Point, VBA)
Experience in using existing statistics/machine learning tools and ability to implement custom algorithms as needed.
Experience in natural language processing tasks/algorithms.
Experience with visualization tools (e.g., PowerBI, Spotfire)
Familiarity with big data technologies (Azure/AWS) is preferred
Web development skills (html, javascript, web frameworks) are not formally required but a working knowledge may be useful to the position
Additional Information
Limited international travel (2 - 4%) will be required
Work hours flexibility to accommodate collaboration across multiple time zones

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.