data science full time senior tech

Job Details

Before you read on, take a look around you. Chances are, pretty much everything you see has been shipped, often multiple times, in order to get there. E-commerce and parcel shipping volumes are exploding but so are customer expectations about shipping speed and cost. Managing shipping and logistics operations to meet increasingly exacting demands is an extremely hard endeavor, especially for SMBs who can be left in the dust by larger and far more sophisticated competitors. But this does not have to be so.

At Shippo, our goal is to level the playing field by providing businesses with access to shipping tools and terms that would not be available to them otherwise. We lower the barriers to shipping for businesses around the world, and move shipping from a pain point to a competitive advantage.

Through Shippo, e-commerce businesses, from fast-growing brands to mom-and-pop shops are able to connect to multiple shipping carriers around the world from one API and dashboard, and seamlessly... run every aspect of their shipping operations, from checkout shipping options to returns.

Join us to build the foundations of something hard yet meaningful, roll up your sleeves, and get important work done everyday. Founded in 2013, and funded by top-tier investors like D1 Capital Partners, Bessemer Venture Partners, Union Square Ventures, Uncork Capital, VersionOne Ventures, FundersClub, we are a fast-growing and proudly distributed Unicorn with hubs in San Francisco and Austin. We are also featured in Wealthfront’s Career Launching List and Forbes’ Cloud 100 list of fast growing startups.

About the Role

As a Senior Data Scientist, you will define, identify, and execute insights empowering our customers to improve operational efficiencies and provide a world-class shipping experience. This will encompass identifying and parsing data, combining data from various sources, conducting exploratory analysis, identifying and visualizing trends, building and validating models, retraining and improving model performance, and getting it ready for deployment in production. The Intelligence team contains both data scientists and software engineers responsible for creating and implementing state-of-the-art machine learning algorithms. The primary responsibility of this role is to assist in algorithm development. Experience with advanced machine learning, experience working with BI tools and a keen analytical mind are key for success in this fast-paced environment.

Responsibilities

  • Develop and build machine learning prototypes to solve business problems using algorithms based on machine learning, statistics, and optimization
  • Partner with engineering/product to productionize those algorithms and create impact in production.
  • Design ML experiments and interpret the results to draw detailed and impactful conclusions.
  • Propose and guide the machine learning framework to drive business insight and facilitate decisions.
  • Establish standard methodologies for data science including modeling, coding, analytics, and experimentation.
    Requirements
  • Graduate degree in Statistics, Economics, Applied Mathematics, Computer Science, Engineering, or other Quantitative Field of Study
  • Expertise in exploratory data analysis, statistical analysis, and testing, and model development using Python and SQL
  • 3+ years work experience in predictive analytics research that drives analytic product innovation and implementation
  • Ability to work efficiently at scale with large data sets
  • Ability to handle multiple mission-critical projects simultaneously while meeting deadlines
  • Exceptional problem-solving skills
  • Excellent oral and written communication skills
    Benefits
  • Benefits: medical, dental, vision, (90% covered by the company, incl. dependents), and pets coverage
  • Flexible PTO + work hours
  • Dog are welcomed in the office
  • 3 VTO days for ShippoCares volunteering events
  • $2,500 yearly learning stipend for your personal growth
  • Free lunch / drinks / snacks
  • Fun team events outside of work hours - happy hours, “escape room” adventures, hikes, and more

See something wrong with this listing?

Contact support