Data Scientist

Company Description
- Suffering from climate anxiety? So are we.
- That's why we developed EcoRail, a software solution for reducing GHG emissions in the rail industry. EcoRail provides crews with real-time driving recommendations to operate their train in the most efficient way possible. Like Tesla did for cars, we strive to do for trains with user-friendly AI technology as we drive the rail industry towards being a fully autonomous system.
- RailVision Analytics is a venture-backed start-up at a seed stage with numerous clients, including VIA Rail and Metrolinx. As we continue to grow our client-base, we are looking to expand our team with enthusiastic, forward-thinking people who want to have a positive impact on the environment through innovation.Why Work With Us?
- Awesome WFH policy with quarterly in-person meetings around the world
- Competitive salaries for quick-learners and fast-paced individuals
- You will have the ability to gain career experience beyond strict job requirements, with decision-making power to be the master of your own projects
- Resources for self-improvement including courses, software, workshops, and conferences
- We are committed to hiring great people from diverse backgrounds, not just because it’s the right thing to do, but because it makes our company stronger

Job Description Overview
The role of a Data Scientist is to ensure the successful development and deployment of ML/Optimization models that can provide safe recommendations for train conductors, making the train operation more efficient and reducing carbon emissions. The Data Scientist will also build the infrastructure to enable future Autonomous Train Operations (ATO). We are looking for a driven, intellectual, and passionate individual with industry experience ready to play a significant role in the company's growth.
Main Responsibilities
- Architect and develop end-to-end Machine Learning/Optimization models, working collaboratively with the Data Science team to optimize train operations in real-world settings.
Lead research effort into improving and enhancing train efficiency models.
Support the development of our train simulator, ensuring its accuracy and a seamless connection with the models and products.
Collaborate with the software development team to integrate ML/RL solutions into RailVision’s products.
- Basic Qualifications
2+ years of relevant work experience.
Degree in an analytical field of study (e.g. Engineering, Physics, Computer Science, Mathematics, Statistics or other relevant fields).
Hands-on experience developing and deploying ML models, data pipelines, and running experiments to validate your models.
Deep understanding of predictive modelling, machine learning, clustering and classification techniques, and common CS algorithms.
Strong working knowledge of statistical techniques (distributions, regressions, error bounds, etc.)
Proficient in Python (i.e. Pandas, NumPy, SciPy, scikit-learn, etc.) or other data science-related tools and libraries.
- Desired Qualifications
Advanced degree in a quantitative field (preferably related to ML/Optimization or Transportation).
Deep understanding or experience with Reinforcement Learning models.
Knowledge or experience in physical simulation systems.
Proficiency with large datasets and time series (SQL, InfluxDB, etc.)
Experience with Python Machine Learning modules such as Keras, TensorFlow, PyTorch.
Knowledge/experience with cloud computing platforms (preferably AWS).
Working experience with some or all the following: Containerization, associated build and deployment CI/CD pipelines
Working experience on a multifunctional agile software development team.
(Bonus) Experience in the rail industry.
Who We Look For
- Creative individuals with the confidence to be a leader and the collaborative nature of a team member
- Driven, self-motivated, and detail-focused individuals
- Clear and concise communicators
- Passion for career growth and continuous learning
- Organized in work habits, schedules, timelines, documentation and correspondence
-Other Details
- Remote work with quarterly in-person meetings (location is voted on every quarter)
- Incentives offered such as Employee Stock Options and yearly bonuses