WHO WE ARE:

Financeit is a point-of-sale financing provider serving some of the largest home improvement and retail organizations in Canada.
Our platform helps businesses close more sales by offering customers affordable monthly payment options for their next big home improvement, vehicle or retail purchase.
We are small enough that you can make an impact within the company and large enough to make an impact in the market.
Financeit is a company where collaboration, inclusivity, fairness, and respect aren’t just ideas that get talked about, but are part of who we are. If such a workplace intrigues you, we hope you’ll join us.

REQUIREMENTS

• University degree in Engineering, Math, or Computer Science
• 2+ years of full-time and/or internship/PEY experience in data engineering, data analytics, dev ops, model ops, applied AI, and/or automation
• 2+ years of applied experience in building data repositories, automating data pipelines and process and/or creating analytic models using tools like dbt, Airflow, Python, and/or Redshift
• Advanced skills in data manipulation, visualization, and modeling, with proficiency in SQL, Looker, and Excel would be highly valued
• Experience working in indirect (B2B2C) lending / consumer credit risk, commercial credit risk, fraud, collections & recoveries and/or in an analytics or automation capacity at a financial institution would be a strong asset
• Strong strategic thinking, judgment, communication (verbal, visual, and written), and advanced problem-solving analytic skills
• Legitimately curious and passionate about finding the “right answer” with a detail-oriented mindset and a “healthy sense of paranoia” about quality
• Highly organized, disciplined and driven, with the ability to manage competing priorities while meeting deadlines.
• Balanced sense of pride & humility with the ability to thrive in a collaborative environment and bring energy and enthusiasm to team culture

ABOUT THE ROLE:

If you’re ready to take your strategic thinking, advanced analytic skills, and knack for digging into the details to the next level, while leaving your mark on a rapidly growing organization, we want to hear from you!
As the Analyst, Risk Data Engineering & Automation, you’ll work under the direction of the Director - Risk Analytics, Data Science & Reporting to ingest and deliver new data sets, build automation pipelines and apply RPA and GenAI to dramatically improve the efficiency & effectiveness of how we record, measure, action and solve risk-related (disputes, fraud, AML, collections, etc.) issues.
Oh, and yes, being fun matters. A lot.

WHAT YOU’LL DO:

• Support projects and initiatives across Risk by identifying, aggregating, transforming and integrating the best data possible into proprietary tools, data warehouses, representative models, and predictive forecasts, as required
• Ensure data quality and accuracy by taking ownership for, and management of, Risk data repositories
• Architect and scale automation (RPA, GenAI, pipelines, etc.) and data infrastructure solutions that drive efficient risk management (credit, fraud, merchant) outcomes
• Contribute to the ongoing development and refinement of accurate operational and financial forecasts (stock-flow, time-series, econometric) that predict consumer & channel partner credit and fraud losses across products, segments, and stakeholders
• Support the development and delivery of on-time high-quality Loss Forecasts and Risk (vintage-level performance), Operational (e.g. Collections performance), Lender (e.g., Portfolio Performance), and Financial (e.g., IFRS) dashboards and reports
• Develop and support the delivery of high-quality automated triggers to notify key partners and stakeholders of the most pressing Risk issues needing their attention
• Support the development, implementation, and deployment of advanced risk prediction and scoring models
• Document data sets, tools, and processes (using tools like Confluence) in ways that ensure clarity and a seamless and accurate internal transfer of knowledge
• Partner with cross-functional strategy, reporting and data science teams to understand their goals and ensure they have what’s needed to succeed and thrive
• Participate in strategic projects and initiatives related to risk management
• Foster a team culture rooted in dedication, curiosity, and continuous improvement