Top Data Science Jobs in Chicago, IL
Collaborate with a team to create machine learning solutions for fraud detection and identity verification, utilizing Python and other tools. Develop, implement, and refine machine learning models to reduce business risks and enhance customer experiences. Document processes, improve frameworks, and generate reports for continuous monitoring of analytical systems.
Building Large Language Models for Enterprise Language Generation at ServiceNow's Advanced Technology Group. Research, propose, implement, and scale LLM's as a key AI-first platform offering. Collaborate with a team to develop high-quality software solutions for customers.
The Manager of Data Engineering at Allies for Community Business is responsible for overseeing data systems, reporting, and compliance requirements. This role involves designing, building, and maintaining data systems, creating reports and visualizations, analyzing data trends, and collaborating with stakeholders to optimize technology stack.
Featured Jobs
Join Square as a Senior Data Scientist in the Payment Risk team. Use advanced statistical techniques to improve risk controls, prevent fraud, and influence product roadmaps. Develop data pipelines, ETLs, and machine learning solutions to protect sellers from bad actors. Collaborate with cross-functional teams to drive innovative risk solutions and enhance the seller experience. Ideal for experienced professionals with a strong background in statistics and machine learning.
As a Decision Scientist at Cash App, apply data-driven techniques to identify opportunities, participate in project definition, and impact business strategy outcomes. Responsible for implementing customer-facing decisions and risk controls using statistical modeling and A/B experimentation. Collaborate with ML teams to inform model evaluations and create offline ML models for decision making. Embedded in the Risk (Cash Card ML) team focusing on automating policies for Cash Card disputes and other transaction types.
Join our world-class Data Science team at Atlassian to drive insights about products and customers. Collaborate with cross-functional partners, apply technical expertise in quantitative analysis, and shape product development. Required qualifications include 8+ years of experience, proficiency in SQL and Python/R, expertise in storytelling with data, and proven impact on business strategy through analytics.
As a Principal Data Scientist in the Application Fraud Team at Capital One, you will work with a cross-functional team to deliver customer-centric products using machine learning technologies. Responsibilities include building machine learning models, leveraging various technologies, and translating complex work into business goals. The ideal candidate is customer-focused, a technical leader, statistically-minded, and a data expert. Basic qualifications include a Bachelor's Degree with 5 years of experience or a Master's Degree with 3 years of experience in data analytics.
Seeking a Director of Data Science to lead a team in leveraging data for business decisions, optimizing marketing strategies, and driving revenue growth. Must have experience in customer lifecycle analysis, digital campaigns, and growth analytics in a SaaS environment. Responsibilities include developing quantitative models, identifying trends, and building data foundations for long-term growth.
Join Arity's Geospatial Data Science team to build scalable distributed machine learning models and extract innovative insights from raw GPS data. Help make transportation smarter, safer, and more useful for everyone by creating actionable insights from geospatial data.
Responsible for providing thought leadership and strategic thinking to solve business problems using analytical techniques. Develop and implement advanced analytics including customer segmentation, optimization, and machine learning algorithms. Deliver presentations of findings and recommendations to leadership. Automate reports and prototype dashboards to provide insights at scale. Continuously improve technical and leadership skills through training and development.
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