Chicago Tech Jobs and Startup Jobs

4

Workforce Planning Analyst (Remote - IL)

Hopper
Chicago
5 days ago
Customer advocacy is at the heart of Hopper. The Workforce Management (WFM) Analyst is vital in ensuring that we have the best possible support for our Air customers. We’re looking for a data-savvy individual to join our Workforce Planning team. Their mission will be to support Air Service Operations to successfully meet its performance targets while optimizing the utilization of people resources to ensure scalable customer satisfaction.

Demand Planning Analyst

Farmer's Fridge
Chicago
6 days ago
+14
Take over all things demand planning at Farmer’s Fridge. This includes daily, weekly, monthly forecasts for all items, fridges, and entire portfolio. Build long-term supplier and production level forecast; Build out long term forecasts to help our production and buying teams. Align with Marketing, Sales, Production, and Operations for demand input. Build out SOP process at Farmers Fridge to align with internal stakeholders. Create and sustain Demand Planning Metrics for Farmer's Fridge. Work with Analytics and Finance teams to generate and maintain Demand Planning metrics. Monitor metrics on daily and weekly basis. Organize Holiday stocking plans; drive process that determines when fridges will be stock around Holidays.

Data Engineer

Farmer's Fridge
Chicago
2 weeks ago
+14
As a data engineer within Farmer’s Fridge’s data engineering team, you will be responsible for helping build out a scalable foundational data platform that will serve the diverse reporting, analytic and decision-making needs of the company. You will be working on a cloud-native, real-time and event-driven architecture with a strong focus on decoupled storage and compute. The foundation that you build will be instrumental in solving our most pressing needs as a business.

Junior Data Scientist

VAMONDE
Chicago
2 weeks ago
+14
The ideal candidate is someone who’s confident in their skills with Python and is aiming to develop a career in Data Science / Machine Learning. You’ve modeled out and implemented complex data structures and are able to explain them to non-technical team members. Ideally, you’ve also worked with AWS or other comparable platforms and are willing to work with us on recommendation engines, data normalization, and user journey insights.

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