Data Scientist II

Metrolinx•Canada,

5d•Onsite

About The Position

Metrolinx is connecting communities across the Greater Golden Horseshoe. Metrolinx operates GO Transit and UP Express, as well as the PRESTO fare payment system. We are also building new and improved rapid transit, including GO Expansion, Light Rail Transit routes, and major expansions to Toronto’s subway system, to get people where they need to go, better, faster and easier. Metrolinx is an agency of the Government of Ontario. At Metrolinx, equity, diversity and inclusion are essential to living our values of serving with passion, thinking forward and playing as a team. This role is an in‑office position (5 days per week) based at our Bay St. location. Our team is highly collaborative, and much of our work benefits from in‑person co‑creation, relationship‑building, and hands‑on partnership with leaders across the organization. We offer flexibility in start and end times while maintaining core business hours for shared availability across the team. Our Marketing Customer Analytics Office is looking for a Data Scientist II to join the team. This individual will be accountable for establishing the analytical methodologies and developing and implementing models for delivering and maintaining Metrolinx ridership & revenue projection under different scenarios (event/sport/marketing performance, B2B/B2C sales, GTM strategy, etc). Model results impacts budget and subsidy plans across the company and are regularly presented to Senior Management, MTO and the Minister’s Office for evidence-based decision making.

Requirements

Completion of a Degree in Statistics, Applied Math, Engineering, Computer Science, or a related discipline – or a combination of education, training, and experience deemed equivalent.
Demonstrated experience in data mining, statistical analysis, and/or predictive analytics. Experience with establishing revenue models in a progressive environment.
Advanced knowledge and working experience with SQL, Python, PySpark /ETL, Power BI with distributed databases and complex data sets.
Statistical analysis (hypothesis testing, A/B Test analysis, etc).
Predictive and prescriptive modeling (understanding the future / forecasting / advice on possible outcomes).
Knowledge/experiences with cloud (Microsoft Azure, Databricks, GCP).
Experience with applied machine learning and modeling.
Proficient in leveraging Microsoft Azure for data handling, analysis and visualization.
Proficient in integrating large and disparate datasets using python.
Proficiency in MS Office (Outlook, Word, Excel, PowerPoint, etc.).
Strong problem solving and critical thinking skills.
Has a passion for continuous learning, and identifies best practices to help increase ridership and revenue.

Responsibilities

Leads the analytical process to predict the impact of GO & UP service levels on ridership & revenue, customer acquisition, retention and loyalty.
Analyze, categorize and forecast special events/sports/sales partnership performance.
Leads the model creation, development and execution process from beginning to end.
Lead analytical initiatives to quantify ridership and revenue impacts of customer-focused business opportunities, including new service introductions, capital infrastructure investments, and customer programs.
Partner closely with Sales and Marketing to deliver actionable insights on Go-To-Market strategies, sports and special event ridership performance, and concert/event demand. Leverage advanced spatial analytics and data science techniques to inform decision-making and drive measurable business outcomes.
Designs and implements end-to-end data pipelines: work closely with stakeholders to build instrumentation and define dimensional models, tables or schemas that support business processes.
Leads analytical efforts to pinpoint opportunities that align with strategic goals, targets, and key performance indicators (KPIs); recommends data-driven solutions and establishes performance metrics to measure the impact and return on investment (ROI) of identified opportunities.
Leads projects, and provides mentorship to other analytics roles throughout the organization.
Ensures best practices are disseminated to the team, and oversee the implementation of innovative and creative ways to source and integrate data or tools to continually advance Metrolinx’s modeling and analytical capability.
Perform data engineering, including ETL, data integration, data contextualization and aggregation, to enable data science work.
Conducts data extraction from relational databases (using SQL/Python), environments.
Crafts raw data and analysis into well-written and persuasive content, establishing recommendations and actions that will support business objectives.
Develops recommendations and oversees the implementation of the recommendations that enhance data governance, data quality and related policies.
Leads Key Performance Indicator (KPI) analysis, presented monthly to SMT, to identify drivers of ridership and fare revenue and inform strategic decisions of service planning and design.