Senior Data Analyst - Activations, Next Best Action

PC Financial•Toronto, ON

1d•CA$75,000 - CA$95,000•Onsite

About The Position

As a Senior Data Analyst on the Activation, Next Best Action team, you will be instrumental in leveraging data, advanced analytics, and modeling to drive critical business outcomes. You will provide key insights that drive Next Best Action strategies across the customer lifecycle, helping optimize onboarding, activation, engagement, and long-term customer growth for banking products. You will leverage data to personalize customer journeys, improve channel performance and profitability, and support effective credit risk management for our credit card portfolio. This role requires a blend of technical expertise, strategic thinking, and strong communication skills to translate complex data into actionable recommendations across various functional teams.

Requirements

Minimum of 3-5 years of progressive experience in data analysis, sales and marketing analytics, financial modeling, or data mining, with a strong focus on extracting actionable insights from large datasets.
Post-Secondary education or equivalent experience in a quantitative field such as Statistics, Mathematics, Computer Science/Engineering, Operations Research, Economics, or Business Administration, coupled with a solid understanding of data analytics principles.
Expert in SQL for querying large, complex datasets (BigQuery Standard SQL is a plus).
Demonstrated experience with statistical software (e.g., SAS, R, Python) and/or programming/scripting languages.
Hands-on experience building and deploying machine learning models for customer segmentation, propensity modeling, and personalization.
Hands-on experience with digital analytics platforms (e.g., Google Analytics, Adobe Analytics) and media platforms (e.g., Google Marketing Platforms, Facebook)
Proficiency in developing reports and interactive dashboards using BI tools (e.g., Tableau, Looker).
Strong understanding of database structures and schemas.
Advanced MS Office skills (Excel, PowerPoint).
Exceptional analytical, problem-solving, and critical thinking skills with the ability to synthesize complex information into clear, actionable recommendations.
Solid understanding of digital marketing and eCommerce best practices.
Proven ability to communicate complex analytical findings and strategic insights effectively, both verbally and in written presentations, to diverse technical and non-technical audiences.
Strong organizational skills and attention to detail, ensuring accuracy and quality in all deliverables.
Ability to manage multiple complex projects, prioritize effectively, and deliver high-quality results in a dynamic, fast-paced environment.
Demonstrated personal accountability and a results-oriented approach.

Nice To Haves

Experience in digital banking, marketing, or credit risk is a significant asset.

Responsibilities

Leverage diverse datasets to generate actionable insights that support Next Best Action (NBA) strategies, optimize onboarding and activation journeys, and drive business growth.
Develop, monitor, and refine NBA strategies across various channels, utilizing advanced analytics, modeling, and statistical testing (e.g., A/B, multi-variate) to optimize profit.
Conduct in-depth analyses of onboarding campaigns, and customer journeys, identifying opportunities for revenue growth and cost reduction.
Design, develop, and present comprehensive reporting (daily, weekly, monthly, quarterly) and automated dashboards (e.g., Tableau, Looker) to monitor key performance indicators and track financial/operational controls.
Collaborate cross-functionally with marketing, product, sales, and media teams to define analytical requirements, implement end-to-end campaign tracking, and deliver customer-focused solutions.
Continuously improve and automate data extraction, analysis, and reporting processes to enhance efficiency and accuracy.
Translate complex analytical findings into clear, concise, and compelling narratives for both technical and non-technical stakeholders, fostering data-driven decision-making.