Machine Learning

Company: COOP COMMERCE INC
Location: San Francisco, California, United States
Type: Full-time
Posted: 04.JUN.2021
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Summary

Co-op commerce was founded in January 2020, with $1.5M pre-seed funding from established VC (Indicator Ventures, Riverpark Ventures, and Bri...

Description

Co-op commerce was founded in January 2020, with $1.5M pre-seed funding from established VC (Indicator Ventures, Riverpark Ventures, and Brian Sugar), to help merchants reduce their reliance on big tech platforms like Amazon and Facebook for customer acquisition. Since January, we've added 350+ brands to our network and are growing very quickly (100%+ MoM).

As Machine Learning engineer at Co-op Commerce you will help co-op commerce solve critical problems for our business model - improving our recommendation engine, personalizing customer shopping experiences, and developing our partnership suggestions. Our wide range of innovative products across post purchase require the creation of machine learning solutions that both fit business needs and drive measurable value for our community of users.

Primary Responsibilities:

• Use co-op commerce's data to build machine learning models that improve our recommendation engine both in partnerships and post purchase suggestions.

• Establish scalable, efficient, and automated processes for data analyses, model development, validation, and implementation.

• Contribute to and promote good software engineering methodologies across the team.

• Collaborate with product and engineering teams to build requirements for new products in relation to data collection and organization which drive actionable insights.

Requirements:

• Degree in a quantitative field such as computer science, engineering, statistics, or decision science

• 2+ years of industry experience

• Experience designing and training machine learning models to solve critical business problems

• Strong programming skills in a scientific computer language (preferably Python)

• Ability to present technical concepts and results in an audience appropriate way

• Persistence, drive, and a passion for building innovative and compelling solutions for data analysis and training

 
Apply Now

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