Strong Analytics is seeking Software and Data Engineers to help design and develop machine-learning based applications for clients ranging from startups to Fortune 500s. Engineers are core contributors at Strong, with responsibilities such as building and managing application pipelines, embedding statistical algorithms in robust software applications, and deploying ML applications to the cloud. The ideal candidate has advanced Python and SQL skills, experience with distributed data processing, and has deployed models in batch, streaming, and real-time API contexts.

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 machine learning scientists and other engineers to develop custom ML solutions for a variety of industries and use cases

• Build machine learning pipelines from ideation up through prototyping, development, and deployment

• Build data pipelines which can ingest, transform, and export data

• Embed statistical algorithms and machine learning models in cloud-based applications
  

• Help identify areas of opportunity and improvement within projects
  

• Collaborate in a fully remote, Agile-like environment using tools like Slack and Git (with a lot of uninterrupted development time)
  

Applicants must reside in either the US or Canada. 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:

• Python

• SQL

• Relational databases (e.g., Postgres, MySQL)

• Distributed computation (e.g., Spark, Hive, Athena)

• Deploying deep learning-based models (e.g., PyTorch/Tensorflow)

• Cloud infrastructures (we use AWS)

• General application (e.g., web API) development

• Git collaboration

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