Lead Machine Learning Scientist

Sorry, this job was removed at 01:45 p.m. (CST) on Tuesday, Aug 20, 2024
Chicago, IL
Agency • Artificial Intelligence • Big Data • Machine Learning • Software • Analytics • Consulting
We are a machine learning research and engineering firm that applies state-of-the-art ML and AI in the real world.
The Role

Strong Analytics is seeking Lead Machine Learning Scientists to collaboratively design and develop machine-learning based solutions for clients ranging from startups to Fortune 500s. Lead ML Scientists are mission-critical at Strong who lead project teams, design project scopes, work directly with clients to iterate on solutions, and ultimately bring together state-of-the-art solutions to our clients' most pressing problems. This is a "player-coach" role, with time for serious technical contributions and team leadership and mentorship.
At Strong, your work will have an immediate impact on clients addressing real world challenges. Our work spans industries such as manufacturing, gaming, agriculture, automotive, and healthcare, among others. We pride ourselves not only in building the right solutions for our clients through research and development, but in implementing and scaling up those solutions through strong engineering. This role thus requires a deep expertise in applying data science and machine learning to real-world problems where data must be gathered, transformed, cleaned, and integrated into a larger architecture.
Responsibilities

  • Work with other machine learning scientists and engineers to develop custom ML solutions for a variety of industries and use cases
  • Develop, train, and validate machine learning algorithms
  • Apply techniques such as classification, clustering, regression, NLP, deep learning (CNN, RNN, GANs), time series forecasting, and Bayesian methods to build scalable solutions
  • Help create generalized solutions out of specific use cases
  • Help identify areas of opportunity and improvement within projects
  • Research new techniques and technologies in the space of ML and AI, and evaluate their potential for business use cases
  • Collaborate in a fully remote, Agile-like environment using tools like Slack and Git (with a lot of uninterrupted development time)


We offer a comprehensive compensation package, including:

  • Competitive salary
  • 100%-covered Health insurance for employees, 75%-covered dependents
  • Four weeks PTO
  • 401(k) with employer contribution matching
  • Personalized monthly perks with matched charitable donations
  • A 100% remote work environment with highly protected work/life balance


Applicants must reside in either the US or Canada and have 3+ years of experience shipping machine learning-based products. All applicants will be considered based on their experience and demonstrated skill/aptitude, not formal education. Candidates will be evaluated based on their experience in the following areas:

  • Statistical modeling and hypothesis testing
  • Designing, training, and validating results from a breadth of machine learning algorithms
  • Writing clean, efficient SQL
  • Building and testing Python applications
  • Building deep neural networks with modern tools, such as PyTorch or Tensorflow
  • Collaborating via Git


Applicants should have the ability to travel infrequently ( 5% of your time) for team meetings, conferences, and occasional client site visits.

The Company
30 Employees
Remote Workplace
Year Founded: 2015

What We Do

We are a collaborative team of machine learning scientists, data engineers, software engineers, and data scientists that bring data- and machine learning-based software to life. We work with organizations of all sizes — from new startups to Fortune 500 enterprises — to tackle design, build, and deploy artificial intelligence and machine learning solutions at real-world scale.

Why Work With Us

We are a learning-driven team that solves problems across industries, from sports analytics to next-generation cars, online safety, and everything in-between. Our goal is to pair the best aspects of a research lab — lots of deep work time, hard problems, and state-of-the-art solutions — with the thrill of shipping real products that change lives.

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