Senior Machine Learning Scientist

TradeRev, Toronto, Ontario, Canada

Revolutionizing Automotive Sales

At TradeRev we use Machine Learning for a wide range of problems, from regression models used for forecasting and prediction, recommender systems based on preference and collaborative filtering, CNNs for object detection and image classification and RNNs for NLP problems.

Working in close collaboration with all internal teams across TradeRev, the Machine Learning Scientist demonstrates the capability to turn data into critical information and knowledge that can be used to make sound organizational decisions. The successful candidate possesses a combination of keen business focus and advanced analytical, problem solving and programming capabilities to quickly cycle hypotheses through models, proposing innovative ways to test and assess scenarios by using data mining approaches and open data on the sets of information available.

Take a look at our benefits here: http://work.traderev.com/

Our Core Values:  Fun. Honest. Accountable. Brave.

As a Senior Machine Learning Scientist, you will be responsible for:

  • Modeling complex enterprise scenarios, discovering enterprise insights and identifying opportunities in the use of statistical, algorithmic, mining and visualization techniques.
  • Communicating results in a way that is customized to the target audience.
  • Collaborating with Data Engineers to build the necessary data pipelines
  • Kicking-off and monitoring training jobs
  • Analyzing the performance metrics of trained models
  • Deploying trained models to production. 
  • Develops experimental design approaches to validate findings or test hypotheses
  • Identifies/creates the appropriate algorithm to discover patterns
  • Provides ongoing tracking and monitoring of performance of decision systems and statistical models
  • Provides business metrics for the overall project to show improvements
  • Converses with, writes reports and creates/delivers presentations to colleagues and peer groups in ways that support problem solving and planning. Explains the context of multiple inter-related situations, asks searching, probing questions, and solicits expert advice prior to taking action and making recommendations.
  • You're also comfortable exploring the data on your own and have an excellent grasp of statistical methods, i.e., calculation of confidence intervals, different techniques to segment data, hypothesis testing and others.

Base qualifications

  • An experienced machine learning scientist who worked on highly scalable systems in an agile environment (5+ years)
  • PhD or Masters Degree in Computer Science/Engineering, specializing in pattern analysis/recognition, machine learning algorithms or related data-science topics
  • Comfort manipulating and analyzing complex, high-volume, high-dimensionality data from varying sources is required
  • Demonstrated ability to propose   solutions to loosely defined business problems by leveraging pattern detection over potentially large datasets.
  • As part of professional experience built and deployed customer- facing machine learning systems
  • A broad understanding of machine learning techniques from linear regression to neural networks
  • You have excellent communication skills and an aptitude for developing relationships at an executive, engineering, and operational levels
  • A strong passion for empirical research and for answering hard questions with data is required
  • Ability to communicate complex quantitative analysis in a clear, precise, and actionable manner
  • Ability to work in a team environment and leading team members.
  • Demonstrating sound judgement and decision-making skills
  • Strong communication and interpersonal skills

Bonus qualifications

  • Deep familiarity with one of AWS, Azure or Google cloud offerings specific to machine learning
  • Experience working with scientific libraries such as Pandas, scikit-learn as well as machine learning frameworks such as Keras, TensorFlow, MXNet or others
  • Experience working with data processing frameworks such as Apache Spark, Kafka or others
We thank all applicants for their interest. Only candidates selected for an interview who are legally authorized to work in Canada will be considered.

TradeRev is an equal opportunity employer committed to diversity.
TradeRev is committed to providing employment in accordance with the Ontario Human Rights Code and the Accessibility for Ontarians with Disabilities Act.  Any assessment and selection materials or processes used during the recruitment process will be available in an accessible format to applicants with disabilities, upon request.  If contacted for an interview, please advise Human Resources if you require disability-related accommodation.

About TradeRev

TradeRev is unique because it was created for dealers by a group of people who love cars and are passionate about the industry. With this came a deep understanding of the age-old process of dealing with trade-ins and the challenges that existed within the sales infrastructure. We believe if the industry as a whole advances and evolves, we can live in a world where when it comes to buying a car, everyone comes out a winner.

 TradeRev Co-Founder Mark Endras recognized these challenges and a truly innovative solution was envisioned: a system that connects dealers all over North America to make moving wholesale inventory quicker, easier and more efficient than ever. The objective was to create technology that powers next-generation automotive marketplaces and, perhaps most ambitious of all, see a world where automotive transactions are fair and easy for everyone. Emboldened by his vision and determined to share his solution, Mark, along with co-founders Wade Chia, Jae Pak and James Tani, worked towards the launch of TradeRev in Toronto in 2011.


Want to learn more about TradeRev? Visit TradeRev's website.