Job Title: Machine Learning Data Scientist
Are you interested in building the next-generation services that will solve complex business problems in the eCommerce fulfillment and supply chain space? We are disrupting the space to provide easy access to fast, economical shipping and delivery experiences to companies big and small and looking for a talented Applied Scientist to design and build a new product from the ground up.
We are looking for an Applied scientist with 5+ years of solid experience in solving complex problems using machine learning and data science. As an Applied Scientist, you will help solve a variety of technical challenges. Given that this is an early-stage initiative, you will play an active role in translating business and functional requirements into concrete deliverables and build quick prototypes or proofs of concept in partnership with other technology leaders within the team.
You will be building machine learning models for a diverse set of eCommerce fulfillment and supply chain-related prediction, classification, and operational problems. You will drive building algorithms for an exciting new space that is just getting started. You will have the opportunity to work with scalable model development tools using SageMaker and other AWS services. Along the way, we guarantee that you’ll learn a ton, have fun and make a positive impact.
Shipium is an equal opportunity employer that is committed to diversity and inclusion in the workplace. We prohibit discrimination and harassment of any kind based on race, color, sex, religion, sexual orientation, national origin, disability, genetic information, pregnancy, or any other protected characteristic as outlined by federal, state, or local laws.
This policy applies to all employment practices within our organization, including hiring, recruiting, promotion, termination, layoff, recall, leave of absence, compensation, benefits, training, and apprenticeship. Shipium makes hiring decisions based solely on qualifications, merit, and business needs at the time.