Who You Are:

You are a highly motivated data scientist or machine learning engineer who will help us reshape consumers’ relationship with their cars. You are eager to join a “full stack” data team that delivers A/B testing, product & growth insights, production quality machine learning models, and the data platform that backs it all. At Fair, you will play a pivotal role in implementing data products across the entire Fair experience, as well as, running high impacting analytics that will help us build toward the best possible experience for our customers.

What You’ll Do:

  • Collaborate across product, engineering, design, marketing, operations, risk & finance teams to optimize the consumer experience and discover high growth opportunities
  • Tell stories using growth & engagement insights to drive new product feature development, marketing campaigns and A/B test experimentation programs
  • Build targeted and personalized consumer marketing campaigns to engage new and current users
  • Explore new data sets and algorithms to improve our consumer risk and vehicle risk models
  • Optimize the user search and vehicle discovery experiences with learning-to-rank ML models and recommendation engines
  • Take machine learning models from R&D all the way to deployed real-time production services
  • Design and develop ML models, explore new prediction algorithms, construct new features, and research new technologies
  • Develop modern data pipeline and warehousing infrastructure
  • Contribute to our machine learning and experimentation platform
  • Participate in bi-weekly white paper reviews, weekly demo days, and code reviews on GitHub
  • Participate in team walks on the Santa Monica Promenade

What You Have

  • Bachelor’s degree in a quantitative discipline; advance degree is a plus
  • Insatiable curiosity and desire to continually expand your analytical and engineering toolkit
  • A keen business & consumer-centric mind
  • Ability to work well in a collaborative (and fun) team environment, and an eagerness to contribute ideas, share skills, and develop best practices

Technologies you can expect to work with:

  • Python, Pandas, SQL-Alchemy, Flask, Jupyter, R, hadleyverse
  • SK-Learn, XGBoost, word2vec, gensim,
  • TensorFlow, SageMaker, DataRobot, Optimizely
  • Tableau, Looker, Amplitude
  • Airflow, Luigi, Spark, DataBricks
  • Snowflake, ElasticSearch, DynamoDB, Postgres
  • Pub/Sub architecture, SQS, SNS
  • Microservices architecture, gRPC, Docker, Kubernetes
  • AWS

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