Elanco Animal Health

Senior Data Scientist

Elanco Animal Health$120K — $145K *
Pharmaceuticals & Biotech
11 - 15 years of experience
Job Overview by Ladders

Qualifications

  • Master's or PhD in a quantitative field (Data Science, Statistics, etc.)
  • 12+ years of experience in Data Science or related work
  • Strong programming skills in Python or R
  • Deep understanding of statistical principles and experimental design
  • Experience applying machine learning techniques to real-world problems
  • Expertise in data visualization and the ability to communicate complex topics clearly

Responsibilities

  • Partner to design and validate statistical and machine learning models
  • Analyze large datasets to extract insights and address business problems
  • Collaborate with business units to apply data science frameworks to their challenges
  • Interpret results and communicate actionable recommendations to stakeholders
  • Use data visualization to present analytical findings effectively
  • Work with Data, AI, and ML Engineers on model deployment
  • Research and apply new methodologies in machine learning and statistics
  • Promote a data-driven culture by mentoring colleagues on data science principles

Benefits

  • Multiple relocation packages
  • Two weeklong shutdowns (mid-summer and year-end)
  • 8-week parental leave
  • 9 Employee Resource Groups
  • Annual bonus offering
  • Flexible work arrangements
  • Up to 6% 401K matching
Full Job Description
Your Role:

As a Senior 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 Enterprise Data Science team, you will partner with stakeholders in Strategy & Innovation, R&D, Manufacturing, Finance, and Commercial, to uncover insights, build predictive models, and create data-driven solutions that directly impact animal health and business outcomes. This role is for a curious and creative problem-solver who is passionate about turning data into tangible value.

This includes four strategic priorities:
  • Pipeline Acceleration: Optimize the search and approval of high impact medicines with a focus on speed, cost and precision.
  • Manufacturing Excellence: Improve the efficiency, quality and consistency of core manufacturing processes, specifically execution and equipment effectiveness.
  • Sales Effectiveness: Simplify the process to find, trust and consume relevant customer insights that drive sales growth and improved engagement.
  • Productivity: Expand operating margin through efficiency by systematically reducing our operating expenses across the company, improving profitability.


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, 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
  • Cross-Functional Problem Solving: Collaborate directly with business units to translate their challenges into data science frameworks. This could include: Strategy & Innovation: Performing market and competitor data analysis. 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. Finance: Analyzing financial data, margin, and profitability performance. 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 research and apply new methodologies in machine learning, statistics, and AI to keep Elanco at the forefront of data science.
  • Champion a Data-Driven Culture: Promote a data-driven culture within Elanco by educating and mentoring colleagues on data science principles and best practices.


What You Need to Succeed (Minimum Qualifications):
  • 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.
  • Programming Proficiency: Strong programming skills in Python or R, with expertise in data manipulation and machine learning libraries.
  • Statistical Rigor: A deep understanding of statistical principles and experimental design, including hypothesis testing, regression, and classification.
  • Machine Learning Experience: Proven experience applying a range of machine learning techniques (e.g., gradient boosting, clustering, NLP, time-series forecasting) to real-world problems.
  • Data Visualization and Communication: Expertise in using visualization tools to create compelling stories and the ability to explain complex topics to a non-technical audience.


What Will Give You the Competitive Edge (Preferred Qualifications):
  • Finance Domain Experience: A strong understanding of financial data, forecasting, budgeting, profitability, and business performance analytics.
  • Business Acumen: A strong ability to grasp business challenges quickly and a passion for connecting data-driven insights to strategic goals. Experience in animal health, 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.
  • Database Skills: Proficiency in SQL for querying and extracting data from relational databases.
  • Cloud Environment Familiarity: Experience working with Public Cloud, specifically Microsoft Azure and Google Cloud Platform (GCP) and their associated data and analytics services is highly desirable.


Additional Information:
  • Location: Global Headquarters- Indianapolis, IN (Hybrid environment)
  • Travel: Minimal


Elanco Benefits and Perks:

We offer a comprehensive benefits package focusing on financial, physical, and mental well-being while encouraging our employees to pursue our purpose! Some highlights include:
  • Multiple relocation packages
  • Two weeklong shutdowns (mid-summer and year-end) in the US (in addition to PTO)
  • 8-week parental leave
  • 9 Employee Resource Groups
  • Annual bonus offering
  • Flexible work arrangements
  • Up to 6% 401K matching

About Elanco Animal Health

Elanco Animal Health is an American pharmaceutical company that develops and produces products for animal health. The company was founded in 1954 and is headquartered in Greenfield, Indiana. Elanco produces a wide range of products for both livestock and pets, including vaccines, antibiotics, and parasiticides. The company operates in more than 90 countries and has a global workforce of over 5,500 employees. Elanco was spun off from Eli Lilly and Company in 2018 and became a publicly traded company in September of that year. The company is listed on the New York Stock Exchange under the ticker symbol ELAN.
Learn more about Elanco Animal Health
Size
9,000 employees
Market Cap
$5.3 billion
Industry
Net Income
-$560 million
5 Year Trend
+10.3%
Revenue
$3.2 billion
NASDAQ

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