Top Remote Senior Level Data Science Jobs in Chicago, IL

As a Lead Data Scientist, you'll design experiments, build predictive models, and lead a team while shaping data-driven strategies to enhance AI deployments.

Lead design, execution, and interpretation of A/B tests and quasi-experiments; apply causal inference methods; partner with product, engineering, and marketing; mentor data scientists; build experimentation frameworks; extract and analyze data using SQL and Python; communicate results to stakeholders.

Lead growth data science initiatives by partnering with Marketing, Sales, and Customer Experience leaders. Develop analyses, experimentation frameworks, and machine learning models for acquisition, engagement, retention, monetization, targeting, segmentation, uplift modeling, and lifetime value prediction. Productionize reliable models with engineering teams, communicate insights to senior stakeholders, establish experimentation best practices, and mentor junior data scientists. The role requires strong business judgment, advanced technical expertise, and experience operating in ambiguous, zero-to-one environments.

Leads advanced data science for pricing, marketing incrementality, customer lifetime value, retention, churn, and commercial decision-making. Designs experimentation and causal inference methods, builds predictive models, productionizes them in Databricks, reviews external analyses, and communicates findings to executives, investors, and the board. Serves as the senior technical authority for experimentation and ensures analyses are reproducible, rigorous, and decision-focused.

Owns high-impact commercial analytics, including pricing and marketing experimentation, causal inference, LTV, CAC, retention, churn, and predictive segmentation models. Sets experimentation standards, productionizes models in Databricks, validates internal and external analyses, and translates rigorous findings for executives, boards, and investors. Partners with Finance, Marketing, Product, Revenue, and Data Engineering while establishing responsible AI-assisted analytical practices.

Conduct workforce analytics and applied research on attrition, engagement, mobility, performance, and planning. Perform statistical analyses, regression modeling, data extraction and validation using SQL and R or Python. Translate HR business questions into actionable insights, communicate findings to stakeholders, and protect sensitive workforce data.

Build reliability and quality models for consumer hardware, analyze manufacturing and telemetry data, develop predictive and decision-support systems, and translate findings into product, quality, firmware, warranty, and supply-chain decisions. The role combines statistical modeling, machine learning, experimentation, data engineering, and cross-functional technical leadership.

Leads and mentors junior developers while designing, modifying, testing, and deploying data solutions in Palantir Foundry. Builds data models and reports from ERP and legacy systems, translates business requirements into technical capabilities, and supports IT modernization. Requires Python, PySpark, cloud architecture, CI/CD, database design, Army domain knowledge, and an active DoD Secret clearance.

Develop marketing measurement strategies, dashboards, data pipelines, attribution analyses, and media mix models. Partner with clients and internal teams to translate business questions into KPIs and actionable recommendations. Build automated data tools, QA processes, and reporting solutions using BI platforms, Python or R, SQL, and marketing data sources. Evaluate AI-assisted tools and support responsible adoption while managing multiple client projects.

Own analytical relationships with travel technology partners, creating scalable reporting on supply, pricing, and performance. Conduct exploratory analysis, apply machine learning and statistical methods, build dashboards, automate recurring workflows with AI tools, and translate complex findings into recommendations for product, engineering, commercial, and executive audiences.