Top Senior Data Science Jobs in Chicago, IL

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.

Lead analytics initiatives to deliver strategic insights for consumer markets. Develop advanced analytics and BI solutions, manage teams, engage stakeholders, implement cloud analytics, and coach diverse teams to improve performance and decision-making.

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.

Lead product analytics efforts by designing and evaluating experiments, building dashboards, and producing statistical insights. Partner with product, design, and engineering to measure product success, identify optimization opportunities, and embed ML-driven personalization into the product.

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.

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.

Lead analytic client engagements to design, develop, and implement predictive and prescriptive models. Partner with sales and business teams to identify opportunities, build data extraction and analysis pipelines (R, Python, SQL, Hive, Spark), present insights, and formalize repeatable processes. Serve as project owner from design through peer review, client presentation, implementation, and audit.

As a Senior Staff Data Scientist, you will lead data science initiatives, mentor teams, develop frameworks for experimentation, and collaborate across departments to drive decision-making through data insights.

Embedded data scientist owning analytics end-to-end for a business unit: define problems and metrics, pull and analyze data, design experiments, build reports, surface insights, and drive recommendations that influence product, growth, and strategic decisions.

Embed on a core business team to define problems, build metrics/reports, run analyses and experiments, and drive data-informed recommendations end-to-end to improve growth, product, AI/automation, or partnerships.

Lead design and delivery of people analytics products using predictive models and language models. Build unified workforce data models, semantic layers, governance, continuous listening & survey frameworks, and enforce experimental and psychometric rigor to inform talent, retention, and team-performance decisions.

The Lead Data Scientist will manage projects on credit risk and business intelligence analytics, leveraging statistical models to provide insights for financial services clients. Responsibilities include developing solutions, leading client engagements, and mentoring junior staff.

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.

Lead development and deployment of scalable data science and ML solutions to detect and mitigate fraud, automate workflows, analyze behavioral signals, run experiments, build dashboards, and partner with stakeholders, legal, and compliance to measure KPIs and integrate models into decision systems.

The Staff Data Scientist will lead data science projects, build ML models, develop AI solutions, and mentor junior staff while integrating data-driven insights into business operations.

Design and deploy predictive forecasting and analytics to support Revenue operations. Build models for forecasting, churn, expansion, and pipeline analytics; create scalable dashboards; partner with Revenue Operations, Finance, and Data Engineering to improve data quality, KPI governance, and executive reporting to drive data-driven decisions and AI readiness.

Own end-to-end modeling for vendor matching, order routing, and supply-chain optimization. Build predictive, causal, RL and OR solutions; design autonomous decision logic; quantify counterfactual impact; ship production models with data engineering; mentor senior data scientists; write technical design docs; partner on quarterly priorities and expand into revenue cycle and finance domains.

Validate and test credit risk models, prepare validation reports and documentation, support model releases and monitoring, automate model training, perform ad-hoc statistical analyses, and communicate findings to stakeholders to support risk management and production deployment.

Senior individual contributor who drives product analytics, experimentation, and applied modeling. Owns growth and performance analyses, designs experiments with robust statistical evaluation, builds repeatable reporting, and partners with Product, Engineering, Operations, Clinical, and Finance to translate data into actionable product and operational decisions.

Owner of analytics for EHR, revenue cycle, and operations: design and run experiments, analyze financial and operational metrics, investigate billing and account issues, and deliver actionable insights to Product, Operations, Finance, and Customer Experience to improve accuracy, reduce friction, and support growth.

Lead design and implementation of AI/ML models, data integration, analysis, and visualization for translational research. Enhance open-source data platforms (Gen3), enforce data governance, mentor junior staff, collaborate with researchers, and translate scientific requirements into production-ready data science solutions.

Design, implement, and maintain marketing inference models (e.g., MMM and attribution). Analyze large datasets and A/B/uplift experiments with rigorous statistics, build predictive and causal models, partner with marketing to generate testable ideas, and communicate insights to drive marketing decisions.

As a Staff Data Scientist, you will analyze large-scale broadband data, develop and validate ML models, and integrate solutions into Calix Cloud, collaborating with teams for enhanced network intelligence and subscriber experience.

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.

Lead and build Neural Earth's geospatial data science function: design and deploy Python-based geospatial models, architect production geospatial data pipelines, validate reproducible methods, translate scientific outputs into customer-ready products, and manage and mentor at least one direct report while advising customers and stakeholders.