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Computational Finance Jobs in Indiana (NOW HIRING)

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Applied Mathematics Tutor

Bloomington, IN · Remote

$18 - $40/hr

Ability to explain modeling techniques for physical systems, approximation methods, and stability analysis while preparing students for engineering, physics, finance, and computational science ...

Amgen

Collaborate with computational and experimental scientists toestablishtheseprocessesasafoundation ... financial plans with opportunities to save towards retirement or other goals, work/life balance ...

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Applied Mathematics Tutor

Fort Wayne, IN · Remote

$18 - $40/hr

Ability to explain modeling techniques for physical systems, approximation methods, and stability analysis while preparing students for engineering, physics, finance, and computational science ...

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Applied Mathematics Tutor

Valparaiso, IN · Remote

$18 - $40/hr

Ability to explain modeling techniques for physical systems, approximation methods, and stability analysis while preparing students for engineering, physics, finance, and computational science ...

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How much do computational finance jobs pay per hour?

As of Sep 3, 2026, the average hourly pay for computational finance in Indiana is $52.27, according to ZipRecruiter salary data. Most workers in this role earn between $44.62 and $70.00 per hour, depending on experience, location, and employer.

What is a computational finance?

A Computational Finance job involves using mathematical models, statistical techniques, and computer algorithms to analyze financial markets, assess risks, and develop trading strategies. Professionals in this field work with large datasets, implement quantitative models, and may develop software for pricing derivatives, portfolio optimization, or algorithmic trading. These roles are common in investment banks, hedge funds, asset management firms, and financial technology companies. Strong programming skills (e.g., Python, C++, R) and knowledge of finance and mathematics are essential for success in this career.

What does a computational finance do?

Professionals in Computational Finance often work on developing and implementing quantitative models for trading strategies, risk management, and pricing of complex financial instruments. They may spend their day analyzing market data, running simulations, optimizing algorithms, and collaborating with traders, risk managers, and software developers. Many roles also involve creating tools to automate workflows and improve the accuracy of forecasts. This work environment is highly collaborative and fast-paced, providing opportunities to contribute directly to financial decision-making and innovation within the company. Over time, successful professionals can progress to lead analysis teams or specialize further in areas such as algorithmic trading or financial engineering.

What are the key skills and qualifications needed to thrive in computational finance?

To thrive in Computational Finance, you need strong quantitative and analytical skills, expertise in financial theory, and typically a background in mathematics, statistics, computer science, or finance. Familiarity with programming languages such as Python, R, or MATLAB, experience with statistical modeling software, and knowledge of financial databases or certifications like CFA are highly valuable. Attention to detail, problem-solving ability, and effective communication make individuals stand out in this field. These skills are crucial for designing complex financial models, interpreting large data sets, and delivering actionable insights to support investment decisions.

What can you do with a computational finance degree?

A computational finance degree prepares individuals for roles such as quantitative analyst, risk manager, or financial engineer, involving tasks like developing models, analyzing financial data, and implementing algorithms. Graduates often work with programming languages like Python, C++, or R and may pursue certifications such as CFA or FRM. The degree provides skills applicable in investment banks, hedge funds, asset management, and financial technology firms.

What are popular job titles related to Computational Finance jobs in Indiana?

For Computational Finance jobs in Indiana, the most frequently searched job titles are:

What job categories do people searching Computational Finance jobs in Indiana look for?

The top searched job categories for Computational Finance jobs in Indiana are:

Computational Finance jobs near you
Infographic showing various Computational Finance job openings in Indiana as of August 2026, with employment types broken down into 91% Full Time, 7% Part Time, and 2% Contract. Highlights an 82% Physical, 7% Hybrid, and 11% Remote job distribution, with an average salary of $108,716 per year, or $52.3 per hour.

Research Scientist - Computational Biologist

Elanco Animal Health Incorporated

Indianapolis, IN • On-site

Full-time

Retirement, PTO

Posted 28 days ago

Elanco rating

7.8

Company rating: 7.8 out of 10

Based on 25 frontline employees who took The Breakroom Quiz

50th of 86 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: Research Scientist - Computational Biologist
As a Research Scientist on our Discovery Research team, you will be at the forefront of Elanco's mission to deliver innovative biologics that improve animal health. You will leverage and develop state-of-the-art AI and structural modeling tools to predict, design, and optimize therapeutic antibodies and proteins. Partnering closely with our principal Computational Scientist and wet-lab teams, you will directly impact the speed and success of our pipeline, helping to create the next generation of animal health therapies. This role offers a unique opportunity to grow your skills in a rapidly evolving field while contributing to tangible, real-world outcomes.
Your Responsibilities:
  • Utilize and develop AI-driven tools (e.g., AlphaFold, Rosetta) to predict and design high-resolution structures of antibodies and other proteins, directly supporting our therapeutic biologics pipeline.

  • Apply generative AI and structural modeling techniques to design novel antibody and protein modalities from scratch, optimizing them for high-precision epitope targeting, affinity, and specificity.

  • Proactively identify and engineer out potential liabilities (e.g., aggregation, immunogenicity) and train novel structure-based ML architectures to enhance the developability of our biologic candidates.

  • Partner closely with wet-lab scientists to analyze experimental data, validate computational predictions, and rapidly iterate on designs to accelerate antibody selection and optimization.

  • Stay current with the evolving AI landscape by evaluating new tools, maintaining thorough documentation, and effectively communicating complex findings to cross-functional teams.

What You Need to Succeed (minimum qualifications):
  • Education: Ph.D. in Computational Biology, Bioinformatics, Structural Biology, Computer Science, or a related field.

  • Experience: 0-3 years of post-graduate experience applying computational methods to biological problems.

  • Top Skills: A strong foundation in structural bioinformatics and AI/ML modeling, with proficiency in a programming language like Python, and the communication skills to work effectively in a cross-functional scientific environment.

What will give you a strong edge (preferred qualifications):
  • Experience with de novo protein design tools, such as diffusion models or physics-based approaches.

  • A track record of applying computational tools to solve biological problems, evidenced by publications or significant project contributions.

  • Familiarity with cloud computing environments (e.g., AWS, GCP) and MLOps principles.

  • Experience in antibody or protein engineering and a foundational understanding of immunology.

  • A proactive mindset with a passion for staying current with the rapidly evolving AI landscape and a motivation to test and evaluate new methodologies.

Additional Information:
  • Travel: Minimal

  • Location: Global Elanco Headquarters - Indianapolis, IN - Hybrid Work Environment

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 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.

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