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Equifax Inc.

Lead Data Scientist - Feature Engineering

Sorry, this job was removed at 12:13 p.m. (EST) on Monday, Jul 28, 2025
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Toronto, ON
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Toronto, ON

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Synopsis of the role

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 are a leader in 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 the Lead Data scientist within the Data & Analytics team at Equifax Canada, you will be critical to driving Data Science innovation, working closely with the rest of the Canadian Equifax Data Science & Insights team and the Data Science community internationally.  You will partner with peers, internal stakeholders and external clients to design and deliver state of the art features / 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, analyse the predictive power and potential business value of varying data types and design proprietary features leveraging these learnings.

What you will do:

  • For the first 3-6 months you will learn our data, our technologies and our platforms and support our advanced analytics team in your journey to becoming an Equifax data expert.

  • You will develop new tools, advanced analytical techniques and products.

  • You will develop new attributes which add value to business decisions including exploratory analysis across new alternative data sources, new data partnerships and expansion of the Equifax data lake.

  • You will design new features to meet the needs of our Scoring and Modelling team, creating packages which offer superior predictive power to those currently being utilised

  • You will manage your own projects including defining business and technical requirements, resource planning and analytical solution design.

  • You will provide recommendations and market insights that support solving complex business problems

  • You will ensure quality control of all analytical output by junior and intermediate data scientists.

  • You will coach and mentor junior and intermediate data scientists in career development and data science skill-set improvement.

What experience you will need:

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

  • 5+ years’ data science and analysis experience with expert knowledge of Python, SQL, R or SAS in a large data environment.

  • 5+ years’ proven hands-on experience designing, building and implementing analytical solutions to solve real world problems. 

  • Experience working with credit or fraud data

  • 1+ years’ background in and an innate talent and passion for trying new technologies and quickly assessing value and implementability within organizations.

  • Bachelor’s or advanced degree in a quantitative discipline such as Engineering, Economics, Mathematics, Statistics, or Physics is essential.

What could set you apart (nice to have skills):

  • A background in financial services, credit, telecommunications or utilities.

  • Experience creating and using advanced machine learning algorithms and statistics

  • Experience in leadership and mentorship

  • 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.

Primary Location:

CAN-Toronto-5700 Yonge

Function:

Function - Data and Analytics

Schedule:

Full time

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