Do you have a passion for being at the forefront of Data Science innovation and building cutting edge, scalable analytical solutions? Are you a tech-savvy individual looking for an exciting, dynamic role to grow your career fast with one of the largest global data analytics and technology companies? Do you want to create new products and push business forward enabling Canadians to live their financial best? If you get excited about designing & developing Machine Learning solutions blending science, art & business logic and unlocking the power of data to solve complex business problems, we would love to hear from you!

As a Data scientist within the Data & Analytics team at Equifax Canada, you will be essential to driving Data Science forward, working closely with the rest of the Canadian Equifax Data Science & Insights team.  You will partner with peers, internal stakeholders and external clients to deliver the best decision science models & attributes that leverage Equifax’s vast data assets. These include decision areas covering the credit lifecycle, geodemographic & marketing attributes, ratings & fraud models, as well as any new areas where data driven decision making can be informed by predictive modeling including advanced modeling techniques and machine learning. You will extract the data you need, create new predictive models, and lead analysis of the data and share insights with peers. 

What you'll do:

• Develop new tools, advanced analytical techniques and products.
• Work with key clients, stakeholders to support development of proprietary analytical products, custom scores and effectively communicate analytical results to key stakeholders using strong data visualizations, superior presentation skills and business language to emphasize the “so what” of the analysis
• Project management including defining business and technical requirements, resource planning and analytical solution design.
• Provide recommendations and market insights that support solving complex business problems
• Ensure quality control of all analytical output.

What experience you need

You don’t have to tick all of the bullets below, but some of the following would be essential:

• 2+ years’ data science experience with strong knowledge of Python or similar and SQL in a large data environment.
• 2+ years’ experience creating and using advanced machine learning algorithms and statistics: regression, simulation, scenario analysis, modeling, clustering, decision trees, neural networks.
• 2+ years’ proven hands-on experience designing, building and implementing analytical solutions to solve real world problems, with limited direct supervision required.
• + years’ experience building models with the best packages including scikit learn, XGBoost, Tensorflow, PyTorch, Transformers.  
• Bachelor’s or advanced degree in a quantitative discipline such as Engineering, Economics, Mathematics, Statistics, or Physics is essential.

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What could set you apart:

• A background in financial services, telecommunications or utilities.
• Experience working with credit or fraud data.
• Experience with development and deployment of models in a cloud based environment such as AWS or GCP is preferred.
• Master’s level degree in a business-related field/MBA.

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