Senior Data Scientist - Batching Algorithms

Hi there! Thanks for your curiosity 👋 We are looking for Senior Data Scientist to join our ML-focused DS team. This role does not do dashboards and short-term analyses but rather focuses on researching and applying the best machine learning models to the problems our products face today. Who we are Retailers all over Latin America spend billions of dollars each year to send thousands of workers to complete tasks like delivering e-commerce orders, stocking shelves, and building displays. Our tech provides these retailers with the manpower for all the above via a smart, gig platform. We are backed by top VCs in San Francisco, Mexico City, and Boston. This is a rare opportunity to build in the Latin America market with a well-funded tech startup with exponential growth. What You Will Do

• Build statistical, optimization, and machine learning models to balance a marketplace of Zubaleros, end-users, and clients.
• Partner with DS-Analytics, Product, and Engineering teams to deliver ML solutions that are appropriately scoped, implemented, and scaled.
• Contribute to the team spirit of always learning, teaching one another, and growing.
• Make solutions that directly impact the tens of thousands of Zubaleros that use our app to make money every day!

• Bachelor’s or higher in Computer Science, Engineering, Mathematics or a related field
• 5+ years of experience in modeling and deploying machine learning solutions in Python
• Demonstrated knowledge of the following domains: classification, regression, clustering, reinforcement learning, computer vision, time series modeling, including some knowledge of the concepts of taking projects to scale in the cloud
• Ability to communicate in business and technical settings. We need to be able to build models and explain to others how and why they work
• You have an interest in the Latin-American Market
• The role can be remote but working hours are generally in the Americas time zones
• You speak English (required) and Spanish (preferred but not required)