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Fintech Data Science Jobs in Chicago, IL (NOW HIRING)

NinjaHoldings

Data Scientist

Chicago, IL · On-site +1

$90K - $130K/yr

Use advanced data analytics to understand consumer risk behavior trends, their impact on the ... Experience working with specialty finance or FinTech * Marketing analytical experience Benefits:

Doist

Senior Data Scientist - Fraud (Hybrid)

Chicago, IL · On-site

$96 - $125/hr

As a Senior Data Scientist on Enova's Fraud Analytics team, you'll be the quantitative engine of ... in fintech or lending * Advanced Python and SQL; experience owning models end-to-end -- design ...

Early Warning Services

Principal Data Engineer

Chicago, IL · Hybrid

$139K - $186K/yr

Be a thought leader: a senior point of expertise on Data Engineering, Data Science, Business ... FinTech domain. * Experience in leading cross-functional teams to create technical solutions.

Apex Fintech Solutions

Accounting Analyst

Chicago, IL · On-site

$61K - $80K/yr

WHO WE ARE Apex Fintech Solutions (Apex) powers innovation and the future of digital wealth ... Bachelor of Science degree in accounting * 1-2 years accounting experience, preferably in a similar ...

Fusion92

Fusion92 Talent Pipeline

Chicago, IL · On-site +1

We unite data scientists, media buyers, copywriters, technologists, developers, consultants, coders ... FinTech Marketing & Client Success - Adoption Marketing Manager, Product Manager, Client Success ...

Fusion92

Fusion92 Talent Pipeline

Chicago, IL · On-site

We unite data scientists, media buyers, copywriters, technologists, developers, consultants, coders ... FinTech Marketing & Client Success - Adoption Marketing Manager, Product Manager, Client Success ...

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Showing results 21-40

All JobsFintech Data Science JobsFintech Data Science Jobs in Chicago, IL

Fintech Data Science information

See Chicago, IL salary details

$38.7K

$126.5K

$202.6K

How much do fintech data science jobs pay per year?

As of Aug 10, 2026, the average yearly pay for fintech data science in Chicago, IL is $126,534.00, according to ZipRecruiter salary data. Most workers in this role earn between $101,500.00 and $140,200.00 per year, depending on experience, location, and employer.

What is a fintech data scientist?

A Fintech Data Scientist is a professional who uses data analysis, machine learning, and statistical techniques to solve problems and create value within the financial technology (fintech) industry. They work with large amounts of financial data to develop predictive models, detect fraud, assess risk, and optimize financial products or services. Their expertise combines knowledge of finance, programming, and advanced analytics to help fintech companies make data-driven decisions and innovate in areas such as payments, lending, and investment. Fintech Data Scientists often collaborate with engineers, product managers, and business stakeholders to deliver actionable insights that drive business growth.

How do fintech data scientists typically collaborate with product and engineering teams to develop new financial products?

In fintech, data scientists often work closely with product managers and engineering teams throughout the lifecycle of a financial product. They analyze user data and market trends to provide actionable insights during the product design phase, and collaborate with engineers to implement machine learning models into the product infrastructure. Regular cross-functional meetings and agile workflows are common, allowing data scientists to iterate on models based on feedback and evolving requirements. This collaborative environment ensures that data-driven solutions are robust, scalable, and aligned with business goals.

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

To thrive as a Fintech Data Scientist, you need a strong background in statistics, machine learning, and programming (often with a degree in computer science, mathematics, or a related field). Familiarity with tools such as Python, R, SQL, cloud computing platforms, and experience with financial data modeling or relevant certifications are typically required. Strong problem-solving skills, attention to detail, and effective communication are important soft skills that set top professionals apart. These skills and qualities are vital for extracting actionable insights from complex financial data, driving innovation, and ensuring regulatory compliance in the fast-evolving fintech industry.

What is the difference between Fintech Data Science vs Fintech Data Analyst?

AspectFintech Data ScienceFintech Data Analyst
Required SkillsAdvanced statistical, programming, and machine learning skillsData interpretation, reporting, and basic analytics
CertificationsData Science certifications, programming coursesData analysis or business intelligence certifications
Work EnvironmentDeveloping models, algorithms, and predictive analyticsData reporting, dashboards, and data cleaning
Industry UsageCreating predictive models for risk, fraud detection, and customer insightsGenerating reports, supporting decision-making with data

Fintech Data Science involves building complex models and applying machine learning techniques, requiring advanced skills and certifications. Fintech Data Analysts focus on interpreting data, creating reports, and supporting business decisions with less technical complexity. Both roles are essential in the fintech industry but differ in technical depth and responsibilities.

What are popular job titles related to Fintech Data Science jobs in Chicago, IL? For Fintech Data Science jobs in Chicago, IL, the most frequently searched job titles are:
What job categories do people searching Fintech Data Science jobs in Chicago, IL look for? The top searched job categories for Fintech Data Science jobs in Chicago, IL are:
Fintech Data Science jobs near you
Infographic showing various Fintech Data Science job openings in Chicago, IL as of August 2026, with employment types broken down into 1% As Needed, 83% Full Time, 12% Part Time, and 4% Contract. Highlights an 87% Physical, 4% Hybrid, and 9% Remote job distribution, with an average salary of $126,534 per year, or $60.8 per hour.

Senior Data Scientist - Fraud (Hybrid)

Enova International

Chicago, IL • On-site

$96K - $125K/yr

Full-time

Posted 13 days ago

Enova International rating

6.8

Company rating: 6.8 out of 10

Based on 5 frontline employees who took The Breakroom Quiz

Job description

We are interested in every qualified candidate who is eligible to work in the United States. However, we are not able to sponsor visas or take over sponsorship at this time.

About the role:

Staying a step ahead of fraudsters takes an inquisitive mind, an appetite to dig deeper, and the imagination to shed new light on how we fight fraud - and here, it all starts with data. As a Senior Data Scientist on Enova's Fraud Analytics team, you'll be the quantitative engine of our fraud prevention effort. You'll develop, enhance, and test the models and pattern-recognition pipelines that surface emerging fraud trends across our lending products - then work hand-in-hand with our Fraud Operations team, who investigate the individual applications your models flag. Their findings (the false positives and false negatives) come back to you to sharpen the identifying characteristics and pivot the approach. It's a fast, iterative loop, and you sit at the center of it.

The broader Enova Analytics department consists of 100 quantitative professionals dedicated to using the latest cutting-edge techniques to drive business value: providing customers with access to fast, trustworthy credit while managing risk. Our company-wide, data-driven culture means you spend less time presenting and more time on the fun part: crunching data.

Key responsibilities:

  • Develop, deploy, and monitor models and pattern-recognition algorithms to detect emerging and shifting fraud trends across one or more lending products
  • Write customized programs in Python for meaningful data analysis and predictive modeling, and query large, complex datasets in SQL
  • Partner closely with Fraud Operations through the full detection loop - pulling data together, surfacing suspicious patterns, and incorporating their investigation results to refine features and reduce false positives/negatives
  • Conduct ad hoc analysis on large, complex datasets to scope new or changing fraud trends and recommend risk, verification, and operational strategies
  • Communicate findings clearly to cross-functional partners, provide requirements, and support implementation
  • Help improve underwriting and verification processes from a fraud-risk perspective
  • Apply AI in production applications to streamline fraud prevention processes
  • Mentor and develop team members, and help coordinate their work with business priorities. 

Requirements:

  • 4+ years of experience in analytics, applied machine learning, or quantitative modeling
  • Hands-on fraud experience required - fraud analytics, fraud strategy, or risk modeling, ideally in fintech or lending
  • Advanced Python and SQL; experience owning models end-to-end - design through deployment and monitoring - on large-scale transactional data
  • Track record of translating analysis into business strategy and communicating with senior stakeholders
  • Aspiration to grow into a people leadership role through mentoring teammates, driving team initiatives, and shaping priorities.

Compensation:

The budgeted annual salary range for this position is $96,000 to $125,000. Actual annual salary will be determined based on qualifications, skills, experience, and level assessed during the hiring process and may fall outside of the range shown. Additional compensation for this role may include a bonus. All full-time employees are eligible to participate in Company benefits, described in more detail here.

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