Data Scientist Jobs in Chicago, IL
Data Scientist jobs in Chicago are in strong demand, concentrated in the Loop, River North, and Fulton Market across financial services, healthcare technology, and logistics analytics. Employers actively hiring include Tempus, PayPal, and Wonder. Scan the live roles below and apply to whichever ones fit.
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Showing 5 of 80+ Data Scientist jobs
ABOUT OUR COMPANY:
Over the years, our mission has expanded to include helping people with other forms of debt - such as refinancing credit cards, which are at all time highs in the US. And we've been able to refinance $6+ Billion in loans through our network of Splash, powered credit union and bank partners who leverage our marketplace and automated loan processing technology. And we've raised over $135 million from investors like partners of DST Global, Citi Ventures, TruStage Ventures, Northwestern Mutual Future Ventures, Detroit Venture Partners, and more.
But at our core, we're still that little company from Cleveland with a big dream: to make people more powerful than their debt and we're just getting started..
ABOUT OUR WORKPLACE:
Splash is remote-first, and proud of it — though our collections team works in-person at our Arizona location.
We spend our days simplifying financial products and getting them into the hands of people who need them most. Right now, we're focused on building financial technologies that fundamentally transform how the industry lends.
Although Splash has been around since 2013, we still operate like a startup — fast-paced, nimble, and full of heart. We're good people who care deeply about doing meaningful work and we approach challenges with creativity, passion, and urgency.
And to hire the best, we provide the best: great health insurance, competitive salaries, and unique benefits like quarterly meet-ups and access to engagement tools that keep us connected — even from afar.
At Splash, everything we do is guided by our values:
Own It – We take full accountability and follow through on commitments.
Raise the Bar – We move fast, innovate faster, and push through barriers.
Say the Hard Thing – We speak up with honesty, respect, and a desire to solve problems and make things better.
Elevate Each Other – We win as a team by lifting each other up.
These values show up in how we work and how we connect — whether we're collaborating on big projects or bonding over everyday moments. Yes, we even have Slack channels for #kids-and-pets and #food because we believe being human makes us better teammates.
ABOUT THE ROLE:
Splash Financial is seeking a Senior/Staff Credit Data Scientist with deep expertise in consumer lending and credit risk analytics. In this role, you will leverage traditional credit bureau data and alternative data sources to develop predictive models, optimize credit and pricing strategies, and drive data-informed decisions that support responsible and scalable lending growth.
The ideal candidate is a proactive, analytical problem-solver who takes ownership of their work and thrives in a collaborative, fast-paced environment. You will apply rigorous statistical methodologies, maintain high standards for data quality and model performance, and approach complex challenges with curiosity and a solutions-oriented mindset. Success in this role requires strong technical expertise, sound judgment, and the ability to translate sophisticated analytical findings into actionable business recommendations.
At Splash, we value accountability, continuous improvement, and open communication. We encourage thoughtful debate, constructive feedback, and a willingness to challenge assumptions while remaining aligned on shared goals. Our team is built on mutual respect, collaboration, and a commitment to delivering meaningful results.
Join a team that values innovation, professional growth, flexibility, and work-life balance. You'll have the opportunity to take ownership of high-impact initiatives, collaborate with talented colleagues, mentor others, and help shape the future of credit decisioning and lending at Splash Financial.
WHAT YOU'LL DO AT SPLASH:
- Develop and deploy statistical and machine learning models to predict credit risk, delinquency, defaults, and loan losses.
- Analyze credit bureau, alternative, and loan performance data to improve underwriting, risk segmentation, and credit decisioning.
- Build quantitative pricing models that optimize risk-adjusted returns, loan performance, and conversion.
- Develop and evaluate AI-powered agents and workflows to enhance underwriting, pricing, and analytical operations.
- Apply advanced statistical methods, feature engineering, and model validation techniques to improve predictive accuracy and reliability.
- Partner with Engineering to deploy scalable, production-ready models and analytical pipelines using Python and other data science tools.
- Monitor model performance, investigate data anomalies, and implement improvements based on changing portfolio trends and realized outcomes.
- Document modeling methodologies and incorporate applicable model governance, fair lending, data privacy, and responsible AI considerations.
- Lead complex data science initiatives, mentor colleagues, and provide constructive feedback on analytical approaches and technical implementations.
- Collaborate cross-functionally with Credit Risk, Product, Engineering, and Finance to translate business challenges into actionable insights and measurable outcomes.
WHAT YOU'LL BRING TO SPLASH:
- Bachelor's degree or foreign equivalent in Statistics, Mathematics, Economics, Computer Science, Data Science, Engineering, or a closely related quantitative field that provides specialized knowledge directly applicable to credit risk and pricing analytics. A Master's degree or PhD in a related discipline is strongly preferred.
- Minimum of 8 years of progressively responsible professional experience in credit risk analytics, pricing analytics, statistical modeling, or related quantitative functions within consumer lending, preferably in unsecured consumer lending or a fintech environment.
- Advanced proficiency in Python, including its application to statistical analysis, predictive modeling, data manipulation, and the development of production-quality analytical solutions.
- Demonstrated expertise in statistical and quantitative modeling techniques, including regression analysis, predictive modeling, feature engineering, model validation, and performance evaluation.
- Strong understanding of consumer lending credit risk and pricing methodologies, including credit decisioning, risk assessment, loan performance analysis, and risk-based pricing optimization.
- Proven ability to apply advanced quantitative methodologies to complex financial datasets, interpret analytical findings, and develop data-driven recommendations that inform credit and pricing strategies.
- Strong communication and collaboration skills, with the ability to translate complex analytical concepts into actionable business insights, provide and receive constructive feedback, and contribute effectively to cross-functional decision-making.
COMPENSATION:
The base salary range for this role is $143,000 to $220,000 annually, based on market data and internal compensation practices. This role may also be eligible for a bonus component tied to individual and company performance. Final compensation will be determined by factors such as location, experience, and skill level.
SPLASHERS ENJOY:
- Fully remote work freedom (for most roles)
- Competitive salary packages
- Flexible PTO + 9 company holidays
- Equity: Share in our start-up success
- Comprehensive and affordable insurance benefits
- Paid parental leave for both caregivers
- Essential modern equipment to get the job done
- Fully paid Claude subscription to supercharge your work
- 401(k) for your future savings
- Quarterly meet-ups: In person & virtual fun
- Awesome Splash swag to flaunt your team spirit
Employment at Splash is based on individual merit. Opportunities are open to all, without regard to race, color, religion, sex, creed, age, handicap, national origin, ancestry, military status, veteran status, medical condition, marital status, sexual orientation, affectional preference, or other irrelevant factors. Splash is an equal opportunity employer.
JOB OFFER & RECRUITMENT SCAM NOTICE
At Splash Financial, we want candidates to feel confident and safe throughout the hiring process. Unfortunately, scammers sometimes pose as employers to trick job seekers into sharing personal information or money.
PLEASE BE AWARE:
- Splash Financial will never ask for payment, banking details, or cryptocurrency as part of our hiring process.
- All legitimate job communications from Splash Financial will come from an @splashfinancial.com email address.
- We do not conduct interviews solely via text message or chat apps.
- Any offer of employment will be made only after a formal interview process and will be sent directly from Splash Financial.
IF YOU RECEIVE A SUSPICIOUS MESSAGE:
- Do not respond or share personal information.
- Do not click on unknown links or download attachments.
- Report the message to careers@splashfinancial.com
ABOUT OUR COMPANY:
Over the years, our mission has expanded to include helping people with other forms of debt - such as refinancing credit cards, which are at all time highs in the US. And we've been able to refinance $6+ Billion in loans through our network of Splash, powered credit union and bank partners who leverage our marketplace and automated loan processing technology. And we've raised over $135 million from investors like partners of DST Global, Citi Ventures, TruStage Ventures, Northwestern Mutual Future Ventures, Detroit Venture Partners, and more.
But at our core, we're still that little company from Cleveland with a big dream: to make people more powerful than their debt and we're just getting started..
ABOUT OUR WORKPLACE:
Splash is remote-first, and proud of it — though our collections team works in-person at our Arizona location.
We spend our days simplifying financial products and getting them into the hands of people who need them most. Right now, we're focused on building financial technologies that fundamentally transform how the industry lends.
Although Splash has been around since 2013, we still operate like a startup — fast-paced, nimble, and full of heart. We're good people who care deeply about doing meaningful work and we approach challenges with creativity, passion, and urgency.
And to hire the best, we provide the best: great health insurance, competitive salaries, and unique benefits like quarterly meet-ups and access to engagement tools that keep us connected — even from afar.
At Splash, everything we do is guided by our values:
Own It – We take full accountability and follow through on commitments.
Raise the Bar – We move fast, innovate faster, and push through barriers.
Say the Hard Thing – We speak up with honesty, respect, and a desire to solve problems and make things better.
Elevate Each Other – We win as a team by lifting each other up.
These values show up in how we work and how we connect — whether we're collaborating on big projects or bonding over everyday moments. Yes, we even have Slack channels for #kids-and-pets and #food because we believe being human makes us better teammates.
ABOUT THE ROLE:
Splash Financial is seeking a Senior/Staff Credit Data Scientist with deep expertise in consumer lending and credit risk analytics. In this role, you will leverage traditional credit bureau data and alternative data sources to develop predictive models, optimize credit and pricing strategies, and drive data-informed decisions that support responsible and scalable lending growth.
The ideal candidate is a proactive, analytical problem-solver who takes ownership of their work and thrives in a collaborative, fast-paced environment. You will apply rigorous statistical methodologies, maintain high standards for data quality and model performance, and approach complex challenges with curiosity and a solutions-oriented mindset. Success in this role requires strong technical expertise, sound judgment, and the ability to translate sophisticated analytical findings into actionable business recommendations.
At Splash, we value accountability, continuous improvement, and open communication. We encourage thoughtful debate, constructive feedback, and a willingness to challenge assumptions while remaining aligned on shared goals. Our team is built on mutual respect, collaboration, and a commitment to delivering meaningful results.
Join a team that values innovation, professional growth, flexibility, and work-life balance. You'll have the opportunity to take ownership of high-impact initiatives, collaborate with talented colleagues, mentor others, and help shape the future of credit decisioning and lending at Splash Financial.
WHAT YOU'LL DO AT SPLASH:
- Develop and deploy statistical and machine learning models to predict credit risk, delinquency, defaults, and loan losses.
- Analyze credit bureau, alternative, and loan performance data to improve underwriting, risk segmentation, and credit decisioning.
- Build quantitative pricing models that optimize risk-adjusted returns, loan performance, and conversion.
- Develop and evaluate AI-powered agents and workflows to enhance underwriting, pricing, and analytical operations.
- Apply advanced statistical methods, feature engineering, and model validation techniques to improve predictive accuracy and reliability.
- Partner with Engineering to deploy scalable, production-ready models and analytical pipelines using Python and other data science tools.
- Monitor model performance, investigate data anomalies, and implement improvements based on changing portfolio trends and realized outcomes.
- Document modeling methodologies and incorporate applicable model governance, fair lending, data privacy, and responsible AI considerations.
- Lead complex data science initiatives, mentor colleagues, and provide constructive feedback on analytical approaches and technical implementations.
- Collaborate cross-functionally with Credit Risk, Product, Engineering, and Finance to translate business challenges into actionable insights and measurable outcomes.
WHAT YOU'LL BRING TO SPLASH:
- Bachelor's degree or foreign equivalent in Statistics, Mathematics, Economics, Computer Science, Data Science, Engineering, or a closely related quantitative field that provides specialized knowledge directly applicable to credit risk and pricing analytics. A Master's degree or PhD in a related discipline is strongly preferred.
- Minimum of 8 years of progressively responsible professional experience in credit risk analytics, pricing analytics, statistical modeling, or related quantitative functions within consumer lending, preferably in unsecured consumer lending or a fintech environment.
- Advanced proficiency in Python, including its application to statistical analysis, predictive modeling, data manipulation, and the development of production-quality analytical solutions.
- Demonstrated expertise in statistical and quantitative modeling techniques, including regression analysis, predictive modeling, feature engineering, model validation, and performance evaluation.
- Strong understanding of consumer lending credit risk and pricing methodologies, including credit decisioning, risk assessment, loan performance analysis, and risk-based pricing optimization.
- Proven ability to apply advanced quantitative methodologies to complex financial datasets, interpret analytical findings, and develop data-driven recommendations that inform credit and pricing strategies.
- Strong communication and collaboration skills, with the ability to translate complex analytical concepts into actionable business insights, provide and receive constructive feedback, and contribute effectively to cross-functional decision-making.
COMPENSATION:
The base salary range for this role is $143,000 to $220,000 annually, based on market data and internal compensation practices. This role may also be eligible for a bonus component tied to individual and company performance. Final compensation will be determined by factors such as location, experience, and skill level.
SPLASHERS ENJOY:
- Fully remote work freedom (for most roles)
- Competitive salary packages
- Flexible PTO + 9 company holidays
- Equity: Share in our start-up success
- Comprehensive and affordable insurance benefits
- Paid parental leave for both caregivers
- Essential modern equipment to get the job done
- Fully paid Claude subscription to supercharge your work
- 401(k) for your future savings
- Quarterly meet-ups: In person & virtual fun
- Awesome Splash swag to flaunt your team spirit
Employment at Splash is based on individual merit. Opportunities are open to all, without regard to race, color, religion, sex, creed, age, handicap, national origin, ancestry, military status, veteran status, medical condition, marital status, sexual orientation, affectional preference, or other irrelevant factors. Splash is an equal opportunity employer.
JOB OFFER & RECRUITMENT SCAM NOTICE
At Splash Financial, we want candidates to feel confident and safe throughout the hiring process. Unfortunately, scammers sometimes pose as employers to trick job seekers into sharing personal information or money.
PLEASE BE AWARE:
- Splash Financial will never ask for payment, banking details, or cryptocurrency as part of our hiring process.
- All legitimate job communications from Splash Financial will come from an @splashfinancial.com email address.
- We do not conduct interviews solely via text message or chat apps.
- Any offer of employment will be made only after a formal interview process and will be sent directly from Splash Financial.
IF YOU RECEIVE A SUSPICIOUS MESSAGE:
- Do not respond or share personal information.
- Do not click on unknown links or download attachments.
- Report the message to careers@splashfinancial.com
See All 80 Data Scientist Jobs in Chicago
Find roles in Chicago that match your experience and apply in just a few clicks.
Find Data Scientist JobsData Scientist Job Market in Chicago
Who's Hiring
Top Industries Hiring
- Banking & Financial Services
- Technology & Software
- Food & Beverage
- Fintech
- Staffing & Recruiting
Data Scientist Jobs in Chicago: Frequently Asked Questions
How do I get a data scientist job in Chicago?
Target Chicago's strongest hiring sectors: financial services firms in the Loop, health systems and medtech companies in the Illinois Medical District, and logistics and supply chain operations tied to O'Hare and the city's distribution infrastructure. Candidates with Python, SQL, and machine learning skills move fastest here. A portfolio built on publicly available Chicago datasets, such as transit or municipal open data, signals genuine local context and stands out with Chicago hiring managers.
Which companies hire data scientists in Chicago?
Companies currently hiring data scientists in Chicago include Tempus, PayPal, and Wonder, per current listings on Migrate Mate as of November 2026. Chicago's mix of legacy financial institutions, fast-growing insurtech and healthtech startups, and major consulting firms means openings exist across company sizes and stages.
Are there remote data scientist jobs in Chicago?
Yes, data science is one of the more remote-compatible analytical roles given its desk-based, software-driven nature. About 89% of data scientist openings tied to Chicago are remote or hybrid as of November 2026, reflecting broad employer flexibility across the market. Modeling, analysis, and reporting work transfers cleanly to remote setups, while roles involving embedded team collaboration or client-facing work in the Loop tend to require more in-office presence.
How can I get a data scientist job in Chicago with little or no experience?
The most realistic entry path in Chicago is targeting junior analyst or associate data scientist roles at mid-size fintech and healthtech companies, which are more likely to invest in developing early-career candidates than large enterprises. Chicago's university partnerships, including programs tied to the University of Chicago and Northwestern, feed entry-level pipelines at local firms. Building a project portfolio using Chicago's open data portal and contributing to local data community meetups in Fulton Market strengthens your candidacy with employers who hire locally.
Which industries hire the most data scientists in Chicago?
The sectors hiring the most data scientists in Chicago are Banking & Financial Services, Technology & Software, and Food & Beverage, based on current listings on Migrate Mate as of November 2026. Chicago's role as a hub for commodities trading, insurance, and large hospital networks drives sustained demand for data science talent well beyond what a typical metropolitan market generates.
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See All 80 Data Scientist Jobs in Chicago
Find roles in Chicago that match your experience and apply in just a few clicks.
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