• Location
    • Los Angeles
  • Date Posted
  • 06 Apr 2020
  • Function
  • Data Science
  • Sector
  • Data

At Factual we love all things data! Our mission is to organize and optimize the world’s location information. As a Data Scientist, you will have the opportunity to shape and influence the direction of our products and propel the growth of our business. You will collaborate with a diverse team of software engineers and data analysts to optimize our current machine learning models and pipelines while also developing creative, data-based solutions. You will be working on many different projects, ranging from scoring the popularity of a place at a given time to pairing anonymized geolocation data with real-world place visits.

About you:

You are passionate about using your programming, data wrangling, and analytical expertise to drive product and business decisions. You are a skilled communicator that will provide thought leadership on metrics, features, and products to teams across the company. You have strong engineering experience and enjoy working in a rapidly changing environment. And most of all: you ship.

What you’ll do:

  • Build models to solve a wide range of location data problems
  • Design experiments and work with fellow engineers to ensure thoroughness and correctness on a variety of analyses
  • Use and commit to our data processing software and frameworks
  • Author specification and lead technical projects
  • Propose creative strategies based on data-driven insights

What we’re looking for:

  • 4+ years of industry experience maintaining production machine learning pipelines and using data science to solve business problems
  • Deep understanding of machine learning concepts and algorithms - particularly classification, clustering, and supervised learning.
  • Expertise with Python/Scala/Java
  • Familiarity with distributed programming with Spark or MapReduce
  • Applied knowledge of Statistics (we really value people who can handle uncertainty and variance)
  • Willingness and ability to wrangle messy data
  • An advanced degree in a quantitative field (Math, Statistics, Computer Science)
  • Excellent oral and written communication skills