elanco
Senior Data Scientist
At a Glance
- Location
- Indianapolis, Indiana, United States
- Employment
- Full time
- Experience
- 2+ years
- Posted
- 2026-08-05
Key Requirements
Required Skills
Domain Knowledge
- Education
- Engineering
Benefits & Perks
We offer a comprehensive benefits package focusing on financial, physical
Requirements
Advanced proficiency in Python (and /or R), SQL, with experience building and maintaining data pipelines in Databricks or similar environments.
Solid foundation in software engineering best practices, including Git, unit and integration testing, CI/CD and model deployment capabilities.
Proficiency in data visualization tools such as Power BI, Tableau or Databricks Dashboard.
Proven ability to deploy and manage high-performance models in production environments using machine learning ops tools and technologies.
Experience building end-to-end observability frameworks, including model monitoring, drift detection, and business performance tracking.
Familiarity with Natural Language Processing, Generative AI techniques (e.g., LLMs, RAG architectures, AI Agents).
Compensation & Benefits
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
Responsibilities
This role is critical in transforming complex data into strategic insights and scalable solutions that drive business value.
The ideal candidate will combine strong expertise in advanced analytics, operations research, and AI/ML with the ability to translate ambiguous business challenges into impactful, production-ready solutions.
Lead end-to-end data science initiatives - from problem definition and data exploration to deployment of scalable, production-grade solutions.
Apply advanced modeling techniques, including machine learning, deep learning, statistical methods and operations research (e.g., optimization, simulation), to solve complex business problems.
Partner with cross-functional business stakeholders to translate strategic objectives into actionable analytical solutions.
Design and develop robust data pipelines and models leveraging platforms such as Databricks, Azure Synapse, and SAP.