We are a team of PhD-trained data scientists with expertise in machine learning, research and analytics, and deploying data-driven applications at scale. We help organizations of all sizes — from new startups to Fortune 500 enterprise firms — tackle challenging analytics and machine learning projects. We work with them frame their problems, design end-to-end solutions, and deploy/monitor analytics dashboards and machine learning pipelines that optimize their operations and help them build smarter products. We are always working on new projects in a variety of industries, including the automotive, pharmaceutical, engineering, healthcare, SaaS, and consumer apps spaces. This leads to a fast-paced, learning-focused environment where we are always learning new things in collaboration with our team (and our clients' teams) in order to provide state-of-the-art solutions that work for our clients.

Strong Analytics

United States

Machine Learning Engineer

Strong Analytics is seeking a full-time, remote machine learning engineer to collaborate with our team building and managing machine learning pipelines, embedding statistical algorithms in robust software applications, and deploying machine learning applications to the cloud.

This role requires advanced Python programming and SQL, distributed data processing (e.g., Spark), and deploying models in batch, streaming, and real-time API contexts.

We offer a comprehensive compensation package, including:

  • Competitive base salary
  • Profit sharing or equity, based on experience
  • 100%-covered Health insurance for employees, 75%-covered dependents
  • Four weeks PTO
  • 401(k) with employer matching
  • Personalized monthly perks and matched charitable donations


Candidates will be evaluated based on their skills with the following technologies/workflows:

  • Python
  • SQL
  • Relational databases (e.g., Postgres, MySQL)
  • Distributed computation (e.g., Spark, Hive, Athena)
  • Cloud infrastructure (we use AWS)
  • General application (e.g., web API) development
  • Git collaboration

All applicants will be considered based on their experience and demonstrated skill/aptitude, not formal education.

Applicants should have the ability to travel infrequently (