Senior Data Scientist

About Us

We are changing the way utilities and industry manage our most precious resource: water. We provide water facilities with an Artificial Intelligence driven platform to help their staff make smarter decisions in real-time when operating their critical processes (i.e. water treatment, pumping etc). In doing so, we are able to help facilities drive down their costs, enhance reliability and reduce risks to public safety.

We are thinking about the future, too: by using AI we are reimagining how the operational staff of the 21st century will interact with critical infrastructure.

The Right Candidate

We are looking for impact-minded people who are passionate about making the world a better place through Artificial Intelligence.  As a Data Engineer in EMAGIN, you will be responsible for building data pipelines behind billions of dollars in critical water infrastructure for Fortune 500 companies. We are looking for ambitious, energetic, and talented individuals to join our purpose-driven community bridging the technical and business worlds to deliver products for the global water sector. You will have the opportunity to lead teams in building mission-critical systems and services for high profile clients globally using cutting-edge cloud technologies in an agile environment.

What You Will Do

  • Lead the development of highly scalable, robust machine learning algorithms. 
  • Oversee the deployment of modelling pipelines for real-time applications.
  • Lead optimization and scaling of in-house time-series related machine learning applications. 
  • Lead the communication across engineering teams to ensure effective collaboration and solidify coding and testing standards. 
  • Participate in the hiring and on-boarding process, providing technical insight. 

What You Will Need

Technical skills:

  • 5+ years experience with Python Data science libraries (numpy, pandas, tensorflow/pytorch, scikit-learn, etc): We use Python and these libraries to build our models and processes. You will need to be able to quickly read and edit code using these libraries. You should know the trade-offs between libraries (Pandas vs. Xarray for time-series data) and how to overcome application bottlenecks.
  • Experience deploying machine learning models with cloud technologies, specifically AWS: We deploy our models/processes to AWS. Having overseen the deployment of several models to production, you know how to leverage AWS technologies to reduce cost and latency.
  • Experience with relational SQL and NoSQL databases: We need you to be able to fetch, process and analyze data using from our databases (PostgreSQL and MongoDB). 

Data-science skills:

  • At least one project creating models for time-series regression/forecasting.
  • Experience with optimization methods including both Stochastic Optimization (i.e. Simulated Annealing, Genetic Algorithms) and Reinforcement Learning.
  • General understanding of machine learning methods.
  • High-level understanding of neural network concepts.

General skills:

  • Demonstrated experience developing production level code.
  • Strong communication and organizational skills. 
  • Experience working with cross-functional teams in a dynamic environment.
  • Adept at translating feature requirements into machine learning solutions.

Why we think you will love working with us

Build something making a difference in the world. Have a big impact at an early-stage, VC-backed software startup. Work with a tight-knit community of experienced entrepreneurs and technologists creating socially-mindful technology. Learn and apply cutting-edge research (Evolutionary Algorithms, Reinforcement Learning, Deep Learning, Model-Predictive Control) to meaningful problems.

Other perks include:

  • Employee Stock Option Plan
  • Competitive Salary
  • Monthly social events
  • Flexible hours
  • Centrally located at the Tannery District in Ontario's Start-up city alongside Google, D2L, Shopify.

If this sounds like your kind of challenge and you have the relevant experience to take them on, get in touch! Please apply with your résumé/CV and any links (GitHub)/attachments about relevant projects and related work.