Lead Data Scientist

San Francisco, CA

KeepTruckin is on a mission to improve the efficiency of America’s trucking industry by connecting the millions of drivers and vehicles that haul freight on our roads. We are backed by Google Ventures and Index Ventures.

In 2015, the U.S. Department of Transportation announced regulation that will require 4.5 million interstate truck drivers to use an Electronic Logging Device (ELD) to record their hours of service with the goal of improving road safety and reducing the paperwork burden on the industry.

With the leading ELD in the market, KeepTruckin is poised to build the largest network of connected commercial vehicles in the world. The massive data generated from this network presents an opportunity to fundamentally change the way the trucking market operates.

We’re looking for a Lead Data Scientist to establish and grow our in-house data science team. As the first data scientist, you would be responsible for identifying opportunities where data can be analyzed in meaningful ways and use the results to guide corrective and/or optimization efforts. You would help identify and implement tools to effectively analyze data and in the long run steer the organization towards adopting a more data-driven approach.

Your responsibilities:

    • Work with product and business teams to identify important questions and answer them with data
    • Apply statistical models and quantitative analysis on large datasets to measure and identify areas for improvement/optimization in the product
    • Lead the effort for collection of new data and refinement of existing data sources
    • Identify and help implement tools to analyze this data effectively
    • Educate and steer the organization towards adopting a more data-driven approach

The ideal candidate has:

    • Bachelor's degree in Computer Science or a quantitative field (e.g., Maths, Economics, Statistics)
    • 4+ years experience in Data Science, Machine Learning and Data Analysis
    • Expert in applied statistics such as distributions, statistical testing, regression, etc
    • Excellent understanding of machine learning techniques and algorithms, such as k-NN, Naive Bayes, SVM, Decision Forests, etc.
    • Expert in data-oriented scripting (e.g. SQL) and statistical programming (e.g., R, Python)
    • Working knowledge of Amazon Web Services is a big plus