Operations Research Decision Scientist

elanco; Indianapolis (IN); Hybrid; USD 160,000 - 230,000; Full time

Benefits offered by this job

Relocation packages

Two weeklong shutdowns in the US

8-week parental leave

401K matching

Job summary

Elanco, headquartered in Indianapolis, seeks an Operations Research Decision Scientist to lead advanced analytics across the value chain in a hybrid role. You will develop and validate ML models, partner with Strategy & Innovation, R&D, Manufacturing, Finance, and Commercial to turn data into actionable business insights.

You will guide strategic planning, optimize operating models, and influence senior stakeholders. A strong background in statistics, ML, and data visualization is required.

Qualifications

• Master’s or PhD in a quantitative field such as Data Science, Statistics, Computer Science, Operations Research, or a related discipline.
• 12+ years experience in Data Science or relevant work.
• Strong programming skills in Python or R, with data manipulation and ML libraries.
• Deep understanding of statistical principles and experimental design, including hypothesis testing, regression, and classification.
• Proven experience applying ML techniques (e.g., gradient boosting, clustering, NLP, time-series forecasting).
• Expertise in data visualization and communicating insights to non-technical audiences.

Responsibilities

• End-to-End Model Development: design, develop, and validate statistical and ML models from data exploration to final analysis.
• Owns, designs, and executes strategic planning and research initiatives to optimize the enterprise operating model using advanced modeling.
• Manages and solves diverse, ambiguous problems with limited guidance.
• Influences solution adoption through stakeholder management at senior levels.
• Data storytelling and visualization to present actionable recommendations.
• Collaborate with Strategy & Innovation, R&D, Manufacturing, Finance, and Commercial to translate challenges into data science frameworks.
• Drive innovation by researching new methodologies and promoting a data-driven culture.

Skills

Python

R

Data manipulation

ML libraries

Statistics

Experiment design

Data visualization

Communication

Education

Master’s or PhD in Data Science/Statistics/CS/Operations Research

Tools

SQL

Job description

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:

As a Operations Research Decision 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.
• Owns, designs, and executes the strategic planning and research initiatives to optimize the enterprise operating model. Applies advanced stochastic, econometric, and simulation modeling to reduce costs and improve profitability.
• Manages and solutions a wide variety of ambiguous, complex, compounding problems given only a skeletal framework or foundation where analytic precedents and guidelines often do not exist.
• Influences solution adoption through exemplary stakeholder management at the most senior levels within the organization.
• 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

Don't meet every single requirement? Studies have shown underrecognized groups are less likely to apply to jobs unless they meet every single qualification. At Elanco we are dedicated to building a diverse and inclusive work environment. If you think you might be a good fit for a role but don't necessarily meet every requirement, we encourage you to apply. You may be the right candidate for this role or other roles!

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

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Elanco is an EEO/Affirmative Action Employer and 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

Elanco may use automated tools, including AI, to support parts of our recruitment process, such as reviewing applications against job-related criteria and/or transferrable skills. These tools help ensure a consistent, structured evaluation, but they do not make hiring decisions. All decisions involve a human reviewer. For more information on how we handle personal data, please see our Elanco Workforce Privacy Notice.