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Financial Data Scientist Jobs in Indiana (NOW HIRING)

Data Engineer

Austin, IN · On-site

$135K - $155K/yr

Work cross-functionally with various departments, including but not limited to: leadership, the development team, the finance team, and the data science team, in order to convert data into ...

... data scientists, optimization and process engineers, capacity planners, supply chain, logistics, finance, data center construction, facility operations, security, network engineering, network ...

Sr. Data Engineer

Indianapolis, IN · On-site

$109K - $131K/yr

The Senior Data Engineer will work closely with analytics, data science, and business stakeholders ... financial wellbeing. * Learning & Development: LinkedIn Learning access; internal opportunities to ...

Enterprises, financial institutions, and developers use Circle to power trusted, internet-scale ... These components power our Product, Engineering, Analytics, and Data Science teams by enabling ...

Showing results 41-60

Financial Data Scientist information

See Indiana salary details

$35.7K

$116.8K

$187K

How much do financial data scientist jobs pay per year?

As of Aug 9, 2026, the average yearly pay for financial data scientist in Indiana is $116,793.00, according to ZipRecruiter salary data. Most workers in this role earn between $93,700.00 and $129,400.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a financial data scientist?

To thrive as a Financial Data Scientist, you need strong quantitative skills, proficiency in statistical analysis, and a background in finance or economics, typically supported by a relevant degree. Familiarity with programming languages such as Python or R, experience with machine learning frameworks, and knowledge of financial databases and tools like Bloomberg Terminal are also important. Critical thinking, problem-solving, and effective communication help you translate complex data into actionable insights for stakeholders. These skills are crucial for building accurate financial models, driving data-driven decision-making, and delivering value in dynamic financial environments.

What is the difference between Financial Data Scientist vs Quantitative Analyst?

AspectFinancial Data ScientistQuantitative Analyst
Required CredentialsDegree in Finance, Data Science, or related fields; often certifications like CFA or FRMDegree in Mathematics, Statistics, Finance; CFA or FRM common
Work EnvironmentFinancial institutions, tech firms, investment firms; focus on data modeling and predictive analyticsInvestment banks, hedge funds, asset management; focus on trading strategies and risk modeling
Employer & Industry UsageUsed across finance and tech sectors for data-driven decision makingPrimarily in finance for trading, risk, and portfolio management

Financial Data Scientists analyze large datasets to develop predictive models and insights, often combining finance knowledge with data science skills. Quantitative Analysts focus on developing mathematical models for trading and risk management. While both roles require strong quantitative skills and finance knowledge, Financial Data Scientists tend to work more on data analysis and machine learning, whereas Quantitative Analysts focus on financial modeling and trading strategies.

What does a financial data scientist do?

A Financial Data Scientist analyzes complex financial data using statistical, machine learning, and computational techniques to identify patterns, forecast trends, and support decision-making within financial institutions. They work with large datasets from sources like market data, customer transactions, and economic indicators to develop predictive models and data-driven strategies. Their work helps organizations manage risk, optimize portfolios, detect fraud, and gain a competitive edge in the financial sector.

How does a financial data scientist typically collaborate with other departments within a financial organization?

Financial Data Scientists regularly work alongside cross-functional teams, including risk analysts, portfolio managers, and software engineers. They collaborate to develop predictive models, automate data pipelines, and translate complex data insights into actionable business strategies. Effective communication is key, as they must explain technical findings to stakeholders with varying levels of data literacy. This collaborative environment not only fosters innovation but also offers opportunities to learn from other experts and expand your professional network.
What cities in Indiana are hiring for Financial Data Scientist jobs? Cities in Indiana with the most Financial Data Scientist job openings:
Infographic showing various Financial Data Scientist job openings in Indiana as of August 2026, with employment types broken down into 1% As Needed, 82% Full Time, 13% Part Time, and 4% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $116,793 per year, or $56.2 per hour.

Data & Analytics Analyst - Affiliates

Brotherhood Mutual

Fort Wayne, IN • On-site

Full-time

Re-posted 12 hours ago


Brotherhood Mutual rating

7.3

Company rating: 7.3 out of 10

Based on 6 frontline employees who took The Breakroom Quiz

235th of 304 rated insurance


Job description

Job Title: Data & Analytics Analyst - Affiliates

FLSA Status: Exempt

Job Family: Affiliates

Department: Strategy & Operations - Affiliates

Location: Corporate Office (Fort Wayne, IN)


JOB SUMMARY
Responsible for the collection, storage, interpretation, and visualization of company and Affiliate data. Serves as team lead in bringing together data sets in visualization tools, and creating views that identify areas for portfolio focus and attention. Key contributor and input into the buildout and execution of the
Affiliate Data & Analytics practice in support of BrotherhoodWorks, Lightwell & ACG Agencies, and BMIC.


POSITION ESSENTIAL FUNCTIONS AND RESPONSIBILITIES
To perform this job successfully, an individual must be able to perform each essential duty satisfactorily. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.

  • Understand objectives, business strategies, and key performance indicators (KPI’s) to provide meaningful management information and analysis to help drive financial and business performance.
  • Develop and maintain Affiliate dashboards through Power BI and other tools.
  • Identify trends, data discrepancies, and/or process improvement opportunities and provide recommended solutions to management.
  • Design, develop and implement predictive and descriptive data mining models to support data driven decision-making.
  • Facilitate development and operationalization of an environment of management information, business intelligence, and decision-making tools for Affiliate team members, and executive leadership.
  • Evaluate and recommend emerging technologies, products, and enterprise-wide solutions.
  • Apply feature selection algorithms to models predicting outcomes of interest, such as product use in the Affiliate niche market.
  • Lead in the production of statistical models, tools, and processes.
  • Deliver oral or written presentations of the results of mathematical modeling and data analysis to management or other end users.
  • Design surveys, opinion polls, or other instruments to collect data.
  • Identify business problems or management objectives that can be addressed through data analysis.
  • Identify relationships and trends or any factors that could affect the results of research.
  • Complete other projects as assigned.


KNOWLEDGE, SKILLS, AND ABILITIES
The requirements listed below are representative of the knowledge, skills, and/or abilities required to perform each essential duty satisfactorily. Reasonable accommodations may be made to enable individuals with
disabilities to perform the essential functions.

  • Possess excellent technical and analytical abilities.
  • Demonstrate experience with analytical software, database user interface and query software.
  • Expertise in data mining, mathematics, statistical analysis, and predictive modeling.
  • Possess skills in looking at things differently, debugging, troubleshooting, designing, and implementing solutions to complex technical issues.
  • Effectively interface with external contacts, Brotherhood employees, managers, and department staff members.


EDUCATION AND/OR EXPERIENCE
List Degree Requirement, Years' Experience, and Certifications

  • Must have a bachelor's degree in an analytically focused area e.g., data analytics, economics, finance, math, computer science, statistics, or related discipline.
  • Must have three to four years of experience in a data science, analytics, or business insights role with some level of experience in the general insurance industry.
  • At least one year of experience with Excel, SQL, and/or a statistical programming language (e.g., Python, R, SAS) is required.
  • Experience in building analytics using data pipelines, data visualization tools, or dashboard creation is desired.
  • A master's degree in data science, computer science, statistics, or related discipline is desired.
  • Experience on resume within the insurance or financial services industries is desired.


Terms and Conditions

This description is intended to describe the general content of and requirements for the performance of this position. It is not to be construed as an exhaustive statement of duties, responsibilities, or requirements.

Because the company’s niche is the church and related ministries market, and because effective service requires a thorough understanding of this market, persons in this position must be familiar with church operations and must conduct themselves in a manner that will neither alienate nor offend persons within this target niche.

Brotherhood Mutual Insurance Company reserves the right to modify, interpret, or apply this position description in any way the company desires. This job description in no way implies that these are the only duties, including essential duties, to be performed by the employee occupying
this position. This position description is not an employment contract, implied or otherwise. The employment relationship remains “at-will”.


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