Data Scientist

Faraday Inc.

Location: Burlington

Type: Full Time

Education: No Ed Requirements

Experience: 3 - 5 Years

At the heart of the Faraday AI platform is a shared machine learning pipeline framework built from the ground up. Our data scientists work with clients and their Faraday account managers to carefully define one or more business goals for deployment on the platform. The pipeline uses these “outcome” definitions to perform ETL, training data formation, feature engineering, model building, validation, scoring, and deployment.

Your team is also responsible for curating the Faraday Identity Graph from upstream data sources, preparing interpretive analysis for clients, and nurturing Faraday’s quantitative culture.

About your role
We’re looking for an expert, curious, relentless, trustworthy data scientist to join us at Faraday. You will pursue a variety of challenges, including:

  • Determining the best predictive approaches to meet clients’ business outcomes.
  • Driving research and development of new algorithms, tools, and methods
  • Communicating and providing context to clients.
  • Improving and maintaining Faraday data science products
  • Being curious—there’s so much we don’t know in the world of data science, and our only guaranteed driver of innovation is the collaborative work of open minds.

You are a methodical, self-motivated individual, capable of keeping your eye on the finish line amidst competing priorities. You have good interpersonal abilities which you will employ regularly, including:

  • Weekly team meetings
  • Transparent project tracking
  • Following security protocols to keep sensitive data safe
  • Supporting account managers with data science expertise

Your credentials
This position requires one of the following, where a relevant degree is indata science, statistics, natural science, mathematics, computer science, or other related field:

  • Relevant Masters and at least two years experience, or
  • Relevant Bachelors and at least three years experience

Your experience

  • You have a foundation in statistical inference
  • You have demonstrated practical applications of data science

Your technical background

  • You are comfortable with Python and SQL
  • You’re familiar with data visualization best practices
  • You have experience with classifier algorithms (e.g. decision tree


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