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Data Scientist, Decision Analytics & Optimization
Company | BioSpace |
Address | Indianapolis, IN, United States |
Employment type | FULL_TIME |
Salary | |
Category | Internet News |
Expires | 2023-07-24 |
Posted at | 10 months ago |
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.
- Collaborate with other analytics team members to review and provide feedback on the analytics work being done and be willing to seek feedback from other team members about your own work.
- Solve complex business and healthcare problems with advanced analytics and AI/ML methods, particularly in finance.
- Maintain a broad understanding of questions and fully engage with teams, bringing an objective voice to the table and facilitating decisions grounded in data.
- Leading the research & development of new methods, determining the best applications and encouraging adoption. This is a hands-on role.
- Stay current with respect to behavioral sciences and simulation, machine learning and other analytics methodologies to maintain proficiency in applying new and varied methods and to be competent in justifying the methods selected.
- Proficiency in programming languages such as R or Python
- Masters in Applied Mathematics, Statistics, Operations Research, Physics, Computer Science, Engineering or quantitative related field OR
- Bachelor’s in Statistics, Operations Research, Physics, Computer Science, Engineering or quantitative related field with five years of hands-on data science experience
- Demonstrable experience in building, programming, and integrating algorithms into production systems.
- Identify opportunities for process improvements and automation to improve patients experience
- Have experience with finance, commercial, and ethics applications, simulation, and/or modeling complex systems.
- Understanding of practical concerns that need to be addressed when applying machine learning and simulation techniques in healthcare.
- Have research experience in agent-based modeling and emergent behavior.
- Strong written and verbal communication skills
- Proven experience producing computationally efficient software to meet real-time requirements.
- Understanding of the scientific theory behind machine learning techniques.
- Experience with Advanced Analytics and AI/ML in cloud environments (e.g. AWS)
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