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Senior Data Scientist, Machine Learning - Product Categorization & Demand Forecasting

Our Mission:

Large marketplaces like Amazon have trained us to expect products delivered to our doorsteps within 1-2 days at no extra cost.  As a result, millions of sellers on other marketplaces are falling behind, unable to cost-effectively deliver products to their customers.  Our mission is to transform the $8-12T fragmented and outdated logistics industry, and build an intelligent, asset-lite network that enables any online seller to offer fast, affordable fulfillment.


Our Team:

How we arrived at Deliverr is different — we are violinists, economists, ex-consultants, journalists, and more.  What unites us together is the Deliverr factor: a bias for action, curiosity, and entrepreneurial ownership.  We're looking for intelligent, driven, and passionate people to help make our vision a reality.  We’re based in the heart of San Francisco and building teams around the globe — backed by leading Silicon Valley venture capital firms.  If you are excited about joining a people-first company that is driven to power the future of online retail, — we're looking for you.  Are you ready?


What you'll do:

  • Designing and developing machine learning systems and models to improve strategic and operational decision-making
    • What product categorization are most relevant for growth, sales and forecasting
    • What products are ordered together
  • Work with business stakeholders to identify and solve novel problems with ML tools
  • Work closely with engineering teams to capture useful data and embed models in production systems
  • Monitoring model performance in changing real-world conditions
  • Fine-tune results with testing and using feedback from customers and stakeholders
  • Research and implement a range of ML algorithms and tools
  • Ongoing strategic thinking to solve the following:
    • What product categorization methods are most relevant for growth, sales, and forecasting? How can Deliverr help its sellers by recommending more product-relevant services and choices?
    • How can Deliverr improve internal decision-making, including inventory placement and promised fulfillment speeds, using product characteristics?
    • Using large streams of sales data from very different e-commerce environments, can Deliverr offer customized guidance to improve seller outcomes?

What we’re looking for:

  • Minimum of an undergraduate quantitive degree in applied statistics, analytics, economics, or similar
  • 3+ years of hands-on experience developing econometric or optimization models with real-world applications to include demand forecasting
  • Experience with SQL and BI tools, required
  • Experience with Python, preferred
  • Background in supply chain logistics, highly desired
  • Proven ability to move between technical modeling tasks and product-oriented questions
  • Precise and concise communication
  • Ability to organize, prioritize, and adapt in a rapid-growth startup


Bonus points:

  • Detailed knowledge of e-commerce or logistics
  • Experience running large-scale experiments
  • Experience with dbt


Must be located in the United States or Canada. This role is remote, ongoing.

Deliverr is featured in LinkedIn's 2020 Top Startups List!

We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, gender identity, sexual orientation, age, marital status, veteran status, disability status or any other legally protected status. Deliverr is committed to providing reasonable accommodations for candidates with disabilities through the hiring process.

Comprehensive benefits for hard working teams.

You’ll have a tough challenge to tackle, so we make sure you’re covered!

Catered Meals
401k Plan
Commuter Benefits
Gym Benefits

Application for Senior Data Scientist, Machine Learning - Product Categorization & Demand Forecasting submitted!

Application for Senior Data Scientist, Machine Learning - Product Categorization & Demand Forecasting

Remote, US or Canada

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