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Senior Machine Learning Scientist Jobs in Indiana

Senior Data Scientist We are seeking a highly motivated and experienced Senior Data Scientist to ... Apply advanced modeling techniques, including machine learning, deep learning, statistical methods ...

Requires a Bachelor's degree in Computer Science, Mathematics, or Statistics, and a minimum of 8 ... Prior success in deploying impactful Machine Learning solutions to large-scale production systems ...

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Senior Machine Learning Scientist information

See Indiana salary details

$63.3K

$105.2K

$156.5K

How much do senior machine learning scientist jobs pay per year?

As of Jun 23, 2026, the average yearly pay for senior machine learning scientist in Indiana is $105,190.00, according to ZipRecruiter salary data. Most workers in this role earn between $87,100.00 and $118,900.00 per year, depending on experience, location, and employer.

What is the difference between Senior Machine Learning Scientist vs Data Scientist?

AspectSenior Machine Learning ScientistData Scientist
CredentialsMaster's or PhD in CS, ML, or related fieldBachelor's or Master's in CS, Statistics, or related field
Work EnvironmentFocus on developing ML models, algorithms, and researchData analysis, visualization, and business insights
Industry UsageUsed in AI-driven companies, tech firms, research labsCommon across industries for data analysis and reporting

While both roles involve working with data, Senior Machine Learning Scientists focus on developing advanced ML models and algorithms, often requiring research and deep technical expertise. Data Scientists typically analyze data to generate insights and support decision-making. The roles overlap but differ mainly in technical depth and focus area.

What are Senior Machine Learning Scientists?

Senior Machine Learning Scientists are experienced professionals who design, develop, and implement advanced machine learning models to solve complex business or research problems. They are responsible for leading projects, mentoring junior team members, and staying updated on the latest AI and data science technologies. Their work often involves analyzing large datasets, selecting the right algorithms, and optimizing model performance for real-world applications. In addition to technical expertise, they often collaborate cross-functionally to align machine learning solutions with organizational goals.

What are the key skills and qualifications needed to thrive as a Senior Machine Learning Scientist, and why are they important?

To thrive as a Senior Machine Learning Scientist, you need expertise in machine learning algorithms, statistical analysis, programming (usually in Python or R), and an advanced degree (often a Ph.D.) in a quantitative field. Experience with tools such as TensorFlow, PyTorch, scikit-learn, cloud platforms, and version control systems is typically expected, along with knowledge of deploying models in production environments. Exceptional problem-solving, communication, and leadership skills help you translate complex data insights into actionable business solutions and mentor junior team members. These skills are crucial for developing innovative models, ensuring robust deployment, and driving impactful data-driven decisions.

What are some common challenges Senior Machine Learning Scientists face when deploying models to production environments?

Senior Machine Learning Scientists often encounter challenges such as ensuring model scalability, maintaining model performance over time, and addressing data drift once models are deployed to production. Collaborating closely with engineering and operations teams is crucial to streamline deployment pipelines and monitor models for real-world reliability. It’s also important to communicate findings and potential risks to stakeholders, and to regularly update models based on new data or business requirements. These aspects make strong cross-functional teamwork and problem-solving skills essential in this role.
What cities in Indiana are hiring for Senior Machine Learning Scientist jobs? Cities in Indiana with the most Senior Machine Learning Scientist job openings:
Infographic showing various Senior Machine Learning Scientist job openings in Indiana as of June 2026, with employment types broken down into 2% Locum Tenens, 50% Full Time, 25% Part Time, 6% Temporary, 15% Contract, and 2% Nights. Highlights an 87% Physical, 6% Hybrid, and 7% Remote job distribution, with an average salary of $105,190 per year, or $50.6 per hour.
Senior Data Scientist

Senior Data Scientist

Elanco

Indianapolis, IN • On-site

Full-time

Retirement, PTO

Posted 5 days ago


Elanco rating

7.8

Company rating: 7.8 out of 10

Based on 25 frontline employees who took The Breakroom Quiz

42nd of 71 rated pharmaceutical


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: Senior Data Scientist

We are seeking a highly motivated and experienced Senior Data Scientist to join our Enterprise Analytics and Governance organization. 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.

Your Responsibilities:

  • 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.
  • Build and maintain interactive dashboards and data products using Databricks dashboard, Power BI or Tableau to enable real-time decision-making.
  • Implement best practices in software engineering, including modular code design, testing, version control, and CI/CD pipelines.
  • Ensure model transparency, explainability and interpretability using Explainable AI (XAI) approaches.
  • Monitor, evaluate, and optimize model performance in production environments, including establishing observability and feedback loops.
  • Communicate complex analytical insights clearly to both technical and non-technical stakeholders.
  • Provide technical leadership and mentorship to junior team members.

What You Need to Succeed (Minimum Qualifications):

  • Education/Required Experience: PhD in Statistics, Data Science, Computer Science, Operations Research or a related STEM field with 2+ year of experience, OR Master's degree with 5+ years of relevant experience.
  • Strong expertise in machine learning, deep learning, statistics and/or optimization.
  • 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.

What Will Give You the Competitive Edge (Preferred Qualifications):

  • 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).
  • Experience working with large-scale enterprise data platforms and cloud ecosystems (Azure, AWS, GCP).
  • Demonstrated ability to operate effectively in ambiguous, fast-paced environments.

Additional Information:

  • Location: Indianapolis, IN Global HQ (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

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 jobrelated 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.


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