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Financial Data Scientist Jobs (NOW HIRING)

Innovizant LLC

Data Scientist

Madison, WI

Innovizant made up of exceptional data scientists and domain experts with a great experience in Our financial services industry solutions include Credit Risk insights, Customer Churn analysis ...

Bread Financial

Lead Data Scientist

Draper, UT · On-site +1

$144K - $250K/yr

Job Summary The Data Scientist role at Bread Financial is responsible for generating data-driven insights to support enterprise data science needs within the organization. The Lead Data Scientist is ...

Bread Financial

Lead Data Scientist

Chadds Ford, PA · On-site +1

$144K - $250K/yr

Job Summary The Data Scientist role at Bread Financial is responsible for generating data-driven insights to support enterprise data science needs within the organization. The Lead Data Scientist is ...

Bread Financial

Lead Data Scientist

Frisco, TX · On-site +1

$144K - $250K/yr

Job Summary The Data Scientist role at Bread Financial is responsible for generating data-driven insights to support enterprise data science needs within the organization. The Lead Data Scientist is ...

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Financial Data Scientist information

See salary details

$37.5K

$122.7K

$196.5K

How much do financial data scientist jobs pay per year?

As of Aug 22, 2026, the average yearly pay for financial data scientist in the United States is $122,738.00, according to ZipRecruiter salary data. Most workers in this role earn between $98,500.00 and $136,000.00 per year, depending on experience, location, and employer.

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.

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.

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 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.

More about Financial Data Scientist jobs

What cities are hiring for Financial Data Scientist jobs?

Cities with the most Financial Data Scientist job openings:

What states have the most Financial Data Scientist jobs?

States with the most job openings for Financial Data Scientist jobs include:

What job categories do people searching Financial Data Scientist jobs look for?

The top searched job categories for Financial Data Scientist jobs are:

Financial Data Scientist jobs near you
Infographic showing various Financial Data Scientist job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 85% Full Time, 11% Part Time, and 3% Contract. Highlights an 85% Physical, 4% Hybrid, and 11% Remote job distribution, with an average salary of $122,738 per year, or $59 per hour.

Data Scientist

Innovizant LLC

Madison, WI

Full-time

Re-posted 12 days ago

Job description

Company Description

Innovizant LLC (headquartered in Chicago, USA) is a leading-edge, global IT Services organization with Sales and delivery offices in Asia. Innovizant LLC, is a Full-service IT provider, focused on delivering Innovative and value driven business analytical solutions leveraging data science, data engineering and decision science to provide winning actionable insights assisting our financial services clients banking, Insurance and credit union business in achieve their business goals.
Innovizant made up of exceptional data scientists and domain experts with a great experience in Our financial services industry solutions include Credit Risk insights, Customer Churn analysis, Customer segmentation, Fraud detection, Asset and Liability analysis, channel optimization analytics, Financial Advisor Network Analytics and product bundling analytics.

Some of our sur accelerators and solution frameworks assist our clients including FIN-CDO (which provided pre-delivered data strategies for the office of Chief Data Officer), BASEL-PRO (for achieving compliance with industry requirements of Basel-BCBS239,) and SmartCECL (Risk mitigation strategies by predicting default and loss given a default)

With data becoming the new 'oxygen' of businesses, many data science consulting firms have evolved in recent times, and they are also contributing the best of their solutions to the modern-day clients. It means today; you can easily find a solution for data sciences. However, the biggest challenge during managing this data comes across in the terms of 'Value Realization'. The true measure of success is to be able to put the data science insights into actionable events.
Many organizations have ended up spending a significant chunk of their analytics budget in some implementing data sciences solution - with minimal to no returns.

Job Description

Role: Data Scientist

Location: Madison, WI

Full Time (Direct Hire)

Job description

         5+ Years of total experience and 2-4 years of in-depth and superlative experience in Data Science.

         Experience in Statistical modeling.

         Candidate will be helping the client to lead this process or improve upon the program.

         Extremely proficient in Data Analysis, data wrangling, model development, software development, A/B Testing, Back Testing.

         Extremely efficient in Python and R.

         Extremely efficient in identifying right analytics model methods and using them. Gradient Boosting, Decision Tree, Regression - are absolutely must.

         Exposure to Insurance (especially consumer Insurance/Retail Insurance) is a minor edge.

         MS in AI/Data Science would also be a plus.

Qualifications

Data Science, Analysis, Python, R, Statistical Modeling, Machine Learning

Additional Information

Thanks & Regards,

Aditya Prakash | Resource Manager | Innovizant LLC

Phone : 630-685-1260

aditya.prakash(AT)innovizant(DOT)com

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