Top Data Science Jobs in Chicago, IL

Consult as a fractional data scientist for hedge funds, private equity firms, and family offices. Lead data science initiatives: build infrastructure, develop and deploy models, create portfolio dashboards, monitor post-deployment performance, and partner with investment teams to turn data into actionable investment insights. Advise on vendor selection, data quality, technology stacks, KPIs, and governance.

Lead research projects that develop and improve data science methodologies and algorithms. Analyze existing solutions, build and test data extraction and transformation architectures, and collaborate with Technology and Product Management on deployment. Investigate production and client data issues, provide data analysis support, maintain SQL, Python, and R code, document processes, and present research findings to internal clients.

Own end-to-end data science for a core business area such as growth, product, AI and automation, or strategic partnerships. Define business problems, metrics, reports, analyses, and experiments; generate actionable insights; communicate recommendations; and drive measurable outcomes with cross-functional stakeholders. The role requires independent analytical work, strong problem-solving, persuasive communication, and ownership of ambiguous initiatives.

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.

Own end-to-end analytical functions for growth, product, AI and automation, or strategic partnerships. Define business problems, metrics, reports, analyses, and experiments; derive insights; communicate recommendations; and drive decisions and measurable outcomes with cross-functional stakeholders. The role requires independent data work, first-principles problem solving, persuasive communication, and ownership of ambiguous initiatives.

Collects, cleans, transforms, explores, and statistically analyzes clinical, financial, and operational data. Builds visualizations and dashboards using tools such as Power BI and Tableau, communicates findings and recommendations to stakeholders, and collaborates with domain experts to evaluate program effectiveness. The role requires healthcare or pharmacy experience, SQL programming, strong analytical skills, attention to detail, and compliance with data privacy regulations such as HIPAA.

As a Staff Data Scientist, you will lead the Platform Data team in building a scalable data platform, collaborate on architecture and solutions, mentor team members, and drive improvements in technology and methodologies.

The Senior Data Scientist will analyze data to drive product strategy, optimize performance, and support product launches, collaborating with cross-functional teams.

As a Senior Data Scientist, you'll develop fraud detection models, perform detailed analyses, and work closely with teams to drive product innovation and business outcomes.

Collects, explores, and analyzes large datasets to identify business opportunities and improve outcomes. Develops predictive models, machine-learning algorithms, testing frameworks, and data pipelines; evaluates data quality and model performance; and communicates actionable insights to stakeholders and clients. The role also manages data science projects, establishes reporting best practices, and collaborates with cross-functional teams to implement and monitor solutions.

Develop machine learning and AI models using clinical, claims, and social determinants of health data to improve pediatric patient outcomes. Partner with stakeholders and cross-functional teams to define requirements, optimize data collection, build data assets, conduct exploratory analysis, and deliver strategic and patient-care insights. Query Snowflake independently and present findings to nontechnical staff.

Analyze and optimize digital partnership performance, growth, profitability, and customer acquisition economics. Design experiments, develop forecasts and performance models, build measurement frameworks, investigate anomalies, and provide actionable recommendations. The role requires translating ambiguous business questions into analytical solutions, communicating insights to technical and non-technical stakeholders, and establishing scalable analytical processes that support strategic decision-making.

Leads analytical and technical execution for member onboarding and customer experience portfolios. Develops advanced analytics, predictive models, causal inference, experimentation, AI/ML, and LLM solutions using Python and SQL. Owns solution design, measurement, testing, and performance evaluation while partnering with cross-functional stakeholders. Mentors data scientists, communicates trade-offs, and applies analytical rigor to improve engagement, satisfaction, retention, and healthcare experiences.

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.

Lead the strategic direction and evolution of Netflix’s company-wide Experimentation Platform. Establish rigorous causal inference and experimentation standards, automate trust and validation practices, consolidate fragmented systems, shape platform product roadmaps, and collaborate with data science and engineering leaders. Translate experimentation needs into scalable tools, influence adoption across teams, mentor colleagues, and ensure reliable experiment allocation, measurement, analysis, and reporting.

Leads end-to-end machine learning model development, from business problem definition and data exploration through deployment, monitoring, documentation, and retraining. Mentors data scientists, collaborates with stakeholders and product teams, troubleshoots production code and ML pipelines, and guides Agile delivery. Requires advanced expertise in statistical modeling, machine learning, cloud platforms, MLOps, production coding, large datasets, containers, version control, and data lakes.

Lead and deliver end-to-end data science projects: design, build, deploy, and monitor ML/statistical models for credit risk, pricing, collections, and fraud. Partner with cross-functional teams to integrate models into production, set model development standards, mentor engineers, and maintain reliable ML pipelines and monitoring systems.

Develop advanced data science and AI/ML solutions using complex healthcare data. Apply statistical modeling, machine learning, NLP, and LLM techniques, including RAG and prompt optimization. Build production-ready workflows integrating models with APIs, data pipelines, enterprise applications, and cloud platforms. Analyze data quality and model performance, communicate findings to technical and executive audiences, and collaborate across product, engineering, clinical, technology, and business teams.

Analyze and characterize conversational audio data, identify underrepresented areas, and build active-learning and human-in-the-loop workflows. Develop representative benchmarks, automate model adaptation, and create reusable data analysis and scoring systems. Partner with research, engineering, and data teams to run experiments, improve models, organize data, and translate complex findings into measurable product improvements.

As a Founding Data Scientist, you will develop predictive models and optimize data infrastructure to enhance supply chain operations, focusing on shipment risk and decision-making.

Leads graph analytics, identity resolution, forecasting, and predictive modeling initiatives for operational, commercial, and product decisions. Designs scalable graph data models, production-ready machine learning solutions, and time-series forecasts. Establishes validation, monitoring, governance, and experimentation practices while partnering with product, engineering, and platform teams. Translates complex analytical findings into business recommendations and provides technical leadership across graph science, forecasting, optimization, and decision-support capabilities.

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.

Build and deploy production-grade LLM applications, AI agents, models, and scalable RAG pipelines for investment and business workflows. Architect secure MCP integrations with enterprise systems, establish MLOps and LLMOps practices, optimize model performance and latency, and develop evaluation, monitoring, governance, and rollback processes. Collaborate with data engineering and platform teams to provide secure, governed access to organizational data.

Partner with product engineering to design and analyze experiments, apply causal reasoning and statistical modeling to marketplace data, and drive data-informed product decisions across the engineering org.

Lead the data science strategy for deployed humanoid robots: build predictive maintenance and reliability models, drive fleet performance and RaaS economics analysis, develop anomaly detection and RCA tooling, link manufacturing test data to field outcomes, and set instrumentation, experimentation, and data-quality standards across hardware, software, manufacturing, and operations.