Data Scientist

407 ETR•Vaughan, ON

26d•CA$85,000 - CA$115,000•Onsite

About The Position

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.

Requirements

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.

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.