At Elanco, the business and/or technical problem is to leverage advanced analytics to solve complex challenges across the entire value chain, optimize pipeline acceleration, improve manufacturing excellence, enhance sales effectiveness, and increase productivity by reducing operating expenses and improving profitability.
Requirements
- Strong programming skills in Python or R, with expertise in data manipulation and machine learning libraries.
- A deep understanding of statistical principles and experimental design, including hypothesis testing, regression, and classification.
- Proven experience applying a range of machine learning techniques (e.g., gradient boosting, clustering, NLP, time-series forecasting) to real-world problems.
- Expertise in using visualization tools to create compelling stories and the ability to explain complex topics to a non-technical audience.
- Proficiency in SQL for querying and extracting data from relational databases.
- Experience working with Public Cloud, specifically Microsoft Azure and Google Cloud Platform (GCP) and their associated data and analytics services is highly desirable.
Responsibilities
- Partner to design, develop, and validate statistical and machine learning models to address key business questions, from initial data exploration to final analysis.
- Lead by example and inspire others, analyzing large, complex datasets to extract meaningful insights and solve business problems. This includes elements of Operations Research, using data to optimize decisions and processes
- Collaborate directly with business units to translate their challenges into data science frameworks. This could include: R&D: Accelerating drug discovery, target identification, clinical trial analysis, and drug repurposing. Manufacturing: Optimizing supply chain logistics and improving production yields through predictive quality control and maintenance. Commercial: Enhancing sales forecasting, pricing and promotions optimization, personalizing marketing campaigns, understanding customer behaviour, and surfacing data insights via large language models.
- Go beyond model building to interpret results, synthesize findings, and communicate actionable recommendations to stakeholders at all levels.
- Use data visualization and clear communication to present complex analytical findings in a compelling and understandable narrative.
- Partner with Data, AI and ML Engineers to ensure that your models are successfully integrated into business processes and applications.
- Continuously research and apply new methodologies in machine learning, statistics, and AI to keep Elanco at the forefront of data science.
Other
- Education: A Master’s or PhD in a quantitative field such as Data Science, Statistics, Computer Science, Operations Research, or a related discipline.
- Required Experience: 12+ years experience in Data Science or relevant work.
- Business Acumen: A strong ability to grasp business challenges quickly and a passion for connecting data-driven insights to strategic goals. Experience in pharma, manufacturing, or commercial analytics is a major plus.
- Industry Experience: A deep understanding of life science, covering the business model, regulatory/compliance requirements, risks and rewards. An ability to identify and execute against opportunities within data science that directly support life science outcomes.
- Location: Global Headquarters- Indianapolis, IN (Hybrid environment)
