Distinguished Data Scientist

At Elanco (NYSE: ELAN) – it all starts with animals!

As a global leader in animal health, we are dedicated to innovation and delivering products and services to prevent and treat disease in farm animals and pets.

At Elanco, we are driven by our vision of Food and Companionship Enriching Life and our purpose – all to Go Beyond for Animals, Customers, Society and Our People.

At Elanco, we pride ourselves on fostering a diverse and inclusive work environment.

We believe that diversity is the driving force behind innovation, creativity, and overall business success.

Here, you’ll be part of a company that values and champions new ways of thinking, work with dynamic individuals, and acquire new skills and experiences that will propel your career to new heights.

Making animals’ lives better makes life better – join our team today!

Your Role: Distinguished Data Scientist


* As a Data Scientist at Elanco, you will be a key driver of innovation and efficiency, using advanced analytics to solve complex challenges across our entire value chain. 


* Reporting to the Global Analytics & Governance team, you will partner with stakeholders in R&D, Manufacturing, and Commercial to uncover insights, build predictive models, and create data-driven solutions that directly impact animal health and business outcomes.

 

Your Responsibilities:


* End-to-End Model Development: Partner to design, develop, and validate statistical and machine learning models to address key business questions, from initial data exploration to final analysis.


* Analytical Thought Leader: Lead by example and inspire others, analysing large, complex datasets to extract meaningful insights and solve business problems.  This includes elements of Operations Research, using data to optimize decisions and processes


* Cross-Functional Problem Solving: 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.


* Generate Actionable Insights: Go beyond model building to interpret results, synthesize findings, and communicate actionable recommendations to stakeholders at all levels.


* Data Storytelling: Use data visualization and clear communication to present complex analytical findings in a compelling and understandable narrative.


* Collaborate on Deployment: Partner with Data, AI and ML Engineers to ensure that your models are successfully integrated into business processes and applications.


* Drive Innovation: Continuously r...