Data Scientist II (6-Month Term, Potential Extension)
About the role
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. 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.
Leads the analytical process to predict the impact of GO & UP service levels on ridership & revenue, customer acquisition, retention and loyalty.
Trains machine learning models to analyze, categorize and forecast service change impacts
Leads the model creation, development and execution process from beginning to end
Oversees work quantifying the potential ridership and revenue impact of customer-centric business opportunities, such as the introduction of new services, the impact of capital builds, and the impact of customer programs
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
Conducts data extraction from relational databases using SQL
Create AI/ML models to improve processes within Innovation and Information Technology and lead KPI analysis that identifies service quality and efficiency of delivery
Crafts raw data and analysis into well-written and persuasive content, establishing recommendations and actions that will support business objectives.
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
Identifying business challenges and developing AI solutions that improve efficiency, automate work, and deliver measurable business outcomes.
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 progressive experience in data mining, statistical analysis, and/or predictive analytics.
Advanced knowledge and working experience with SQL, Python, PySpark Power BI
Proficient in leveraging Microsoft Azure and Azure Databricks for data engineering, large scale data processing, advanced analytics and visualization
Expertise in prompt engineering and leveraging generative AI tools and AI-powered assistants to accelerate data analysis, automate reporting, streamline business workflows, and improve operational efficiency
Statistical analysis (hypothesis testing, A/B Test analysis, etc)
Predictive and prescriptive modeling (understanding the future / forecasting / advice on possible outcomes)
Demonstrated applied machine learning modeling experience
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
Metrolinx is an equal opportunity employer and committed to a diverse and inclusive workforce. We are also committed to offering reasonable accommodation to job applicants in accordance with applicable legislation. If you require assistance or an accommodation at any point during the hiring process, please contact us at: 416-202-5601 or email [email protected].