Top Data Science Jobs in Chicago, IL

Build and validate predictive lending models, analyze consumer risk and portfolio impact, implement and monitor models with engineering, develop tooling and automated SQL/Python dashboards, design A/B tests, and communicate actionable insights to senior management.

As a Data Scientist, you will analyze data, build machine learning models, and collaborate with cross-functional teams to enhance customer offerings within the Discover Card portfolio.

Lead AI and GenAI data science engagements: perform advanced analytics, build predictive models, design data pipelines and warehouses, validate large datasets, produce data visualizations, coach teams, and advise clients on data-driven solutions and systems-level opportunities.

The Data Scientist will analyze complex datasets, build predictive models, collaborate with stakeholders, and present insights for business decisions.

As a Principal Associate, Data Scientist, you will develop machine learning models and analytics to combat money laundering, collaborating with a cross-functional team and modernizing risk management practices.

Build and maintain pricing and profitability models to optimize lending strategies, incorporating proprietary credit models. Design A/B tests, analyze financial performance trends, and present data-driven recommendations to senior management. Collaborate with credit risk, capital markets, FP&A, marketing, and sales to quantify financial impact and improve pricing decisions.

Lead teams applying advanced data science and machine learning to large-scale claims, clinical, and member data to generate actionable insights that reduce cost of care and improve population health. Manage client relationships, mentor staff, ensure project delivery and quality, develop payer-focused analytics products, present findings to senior stakeholders, and promote continuous improvement and knowledge sharing.

The Senior/Staff Data Scientist will build and deploy predictive models for consumer decisioning and business optimization, focusing on machine learning and statistical modeling. Responsibilities include model development lifecycle, data exploration, collaboration with teams, and improving product outcomes.

The Data Scientist will develop predictive models, conduct exploratory analysis, collaborate with teams, build data pipelines, and create visualizations to drive decision-making.

The Data Scientist will develop analytic solutions and predictive models for TransUnion's clients in financial services and insurance. They will engage with clients, lead projects, and deliver insights using advanced programming and statistical techniques.

Lead end-to-end pricing experimentation and strategy for consumer and business products. Design and analyze A/B tests, build pricing models and production-grade data pipelines, partner cross-functionally, and present actionable recommendations to senior leadership.

The Senior Associate, Data Scientist will partner with cross-functional teams to identify risks associated with models and validate machine learning models across the enterprise, enhancing decision-making while ensuring model governance and risk management.

Build and validate predictive models, analyze large structured and unstructured datasets, generate business insights, present analytic results to stakeholders, and develop tools to advance analytics capabilities.

The Senior Data Scientist will manage end-to-end data science efforts, ensure stakeholder trust through timely analysis, and build systems for reproducibility while collaborating with various teams.

Lead Data Scientist partners with business leaders to identify opportunities, design, develop, and deploy advanced analytics and ML solutions. Responsibilities include data preparation, modeling, feature engineering, delivering insights and visualizations, establishing standards, and directing associate data scientists, contractors, and consultants to produce measurable business value.

This role involves onboarding clients, solving scientific problems, guiding data analysis on the Tempus platform, and creating documentation. Requires expertise in biomedical datasets and programming.

Work on Decision Sciences to design and execute statistical analyses and ML studies, wrangle large datasets, produce insights and visualizations, partner with stakeholders, and present results to improve clinical programs and ROI.

Lead product analytics to inform strategy and optimize user experience: translate business questions into analysis, build reliable analytics infrastructure, run A/B tests and ML/statistical analyses, track funnels and cohorts, support 0-to-1 product launches, and communicate actionable insights to cross-functional teams.

Embedded in a core business area, you'll define problems, build analyses, metrics, reports and experiments, surface insights, and drive data-informed product, growth, AI, or partnerships outcomes end-to-end.

Embedded on a core business team, the Associate Data Scientist defines questions, builds metrics/reports, runs analyses and experiments, surfaces insights, and drives data-informed recommendations end-to-end to impact product, growth, AI/automation, or partnerships.

Embedded data scientist owning analytics for a core business area: define problems, build metrics/reports, run analyses and experiments, surface insights, and drive data-informed decisions end-to-end.

Embedded on a core business unit, you will define problems, build metrics, run analyses and experiments, surface insights, and drive data-informed decisions end-to-end across growth, product, AI/automation, or partnerships.

Embedded within a core business area, you will define the right problems, design metrics and experiments, pull and analyze data, build reports, and surface insights. You will make recommendations, secure stakeholder buy-in, and drive execution to improve product, growth, automation, or partnership outcomes.

Embed with a business unit to define problems, build metrics/reports, run analyses and experiments, surface insights, and drive data-informed product, growth, AI, or partnership outcomes end-to-end.

The Data Scientist will advance baseball analytics by developing machine learning models, innovating analytical approaches, and extracting actionable insights from complex data.