Data Scientist

Title: Data Scientist

Department: Data Science and Analytics

Location: 6300 Steeles Ave West, Woodbridge

Total Potential Compensation: $85,000-$115,000

Position Summary:

The successful candidate will assist in leveraging customer, digital, and transportation datasets to create insights on pricing, marketing, and customer travel behavior. The Data Scientist will assist the Director of Data Science and other key stakeholders in bringing actionable data driven solutions to 407 ETR.  This job involves model design, data management, data queries, and providing input into programs and policies. This position is part of a highly collaborative and energetic team in a start-up minded environment.

Duties and Responsibilities:

• Assemble and analyze data to understand customer behavior from existing 407 ETR data, external data sources and emerging sources.

• Building Promotions, Loyalty and Pricing models and optimization using python, pyspark, Gurobi and the like in our Databricks environment.

• Undertake analysis of target customer groups (segments) for promotions, loyalty and pricing programs and assess opportunities and strategies for marketing.

• Ad hoc analysis and modeling of data.

• Lead project-based work with key business stakeholders.

• Build customer analytic models such as: targeting, propensity, price elasticity, attrition, lifetime value, churn and segmentation.

• Develop and measure effectiveness of promotions, loyalty and pricing using methods such as A/B testing, etc.

• Ability to understand business stakeholder’s issues and create valuable insight.

• Present complex models and insights to stakeholders in common language

• Support the Department along with the Information Technology Management Department in planning the structure and storage of new customer related data fields.

Qualifications:

• Experience with Python, SQL, Tableau/PowerBI, AWS Sagemaker, MLFlow, Databricks and AWS cloud.

• A University degree in Engineering, Statistics, Mathematics, or Computer Science.

• Minimum 3-5 years working experience with data science techniques: clustering, regression models, classification, anomaly detection and other machine learning techniques.

• Strong experience building customer analytic models like: targeting, propensity, price elasticity, attrition, lifetime value, churn and segmentation.

• Well-developed business analysis, research and creative problem-solving skills.

• Organizational skills and time management skills; planning and project management, and ability to meet multiple deadlines.

• Ability to explain complex models into common language.

• Strong communication skills and work ethic.

• Highly collaborative team player with an entrepreneurial spirit.

We are actively seeking to fill this role as it is a current vacancy.

About 407 ETR

Highway 407 ETR is an all-electronic open-access toll highway located in the Greater Toronto Area in Ontario, Canada. The highway spans 108 kilometres from Burlington in the west to Pickering in the east. 

407 International Inc. is the sole shareholder of 407 ETR and is owned by: 

• Cintra Global S.E., a subsidiary of Ferrovial S.A. (48.29%)

• Canada Pension Plan Investment Board (CPP Investments) and other institutional investors with non-controlling interests (44.20%)

• Public Sector Pension Investment Board (PSP Investments) (7.51%)

Learn more at 407etr.com

Note: At 407 ETR, we are committed to fostering a diverse, equitable, and inclusive work environment. We value the unique perspectives and backgrounds of all individuals, and we firmly believe that our individual differences make us stronger as a whole.

Our commitment to inclusion extends beyond recruitment and encompasses an inclusive workplace culture through raising awareness, ongoing training, and encouraging feedback. We aim to create a safe and supportive environment where all employees can thrive.

Accommodation for disabilities or other grounds protected by human rights legislation are available upon request for candidates taking part in all aspects of the employment selection process.