Top Tech Jobs & Startup Jobs in Chicago, IL

The Manager, Cloud and Data will lead a team to build and maintain scalable data infrastructure for autonomous vehicle technology, mentoring team members and managing day-to-day operations.

As a Forward Deployment Engineer, you'll translate business needs into technical architectures, prototype AI applications, and integrate solutions while collaborating with teams to drive transformations.

The Customer Success Manager at SimScale drives post-sales lifecycle for customers, ensuring product success, managing relationships, and executing strategies for customer retention and business growth.

The Sales Enablement & Content Specialist will empower sales teams by creating content, training, and processes. They will enhance sales effectiveness through documented methodologies, program design, and ongoing analysis of enablement performance.

The Senior Customer Experience Specialist resolves pharmacy-related issues, supports the EQUIPP® platform, collaborates with stakeholders, and enhances quality performance.

Design and implement supply chain solutions using Manhattan Active TMS, analyze requirements, configure software, and provide client support.

Invitation to join Pathpoint's Talent Community to share your interests, qualifications, and reasons for joining. Submissions are reviewed for future openings across multiple functions; membership does not guarantee interviews but keeps your information on file for relevant opportunities.

As a Software & Data Engineer, you will design data pipelines, deploy AI tools, build data warehouses, and integrate systems for clients, ensuring data quality and performance.

Lead end-to-end patient activation and long-term retention programs, owning activation and retention KPIs. Build and optimize automated onboarding and multi-channel retention journeys, run A/B and multivariate tests, develop segmentation and cohort analytics, partner with Product, Clinical Ops, Fulfillment, and Data Science for churn modeling and delivery issues, and manage retention P&L to improve LTV and reduce churn.

Lead design and production deployment of ML models focused on pricing, availability, forecasting, and optimization. Build data infrastructure, governance, testing/monitoring, and dashboards. Partner with executives and cross-functional teams, mentor others, and establish scalable data-science practices and experimentation frameworks.