Manager, Risk Modelling & Analytics, Forecasting

Financeit; Toronto; On-site; CAD 120,000 - 180,000; Full time

Job summary

Financeit is seeking a Manager of Risk Analytics & Modeling - Forecasting to lead time‑series forecasting, build predictive models, and automate forecasting processes. You will translate macroeconomic signals into actionable insights for planning and decision making, partnering with finance, credit, and risk teams across Canada.

You bring 5+ years of analytics and 4+ years in building models with Python, SQL, and data pipelines, and you enjoy turning complex behaviour into explainable forecasts

Qualifications

• Advanced analytics, data science, and automation skills.
• Strong forecasting and financial modelling experience.
• Experience building scalable data pipelines.

Responsibilities

• Build and refine risk, valuation, and borrower-level models.
• Forecast cashflow and profitability for credit and fraud losses.
• Deliver high-quality loss forecasts daily to executives.
• Develop explainable models linking data to real-world events.
• Improve efficiency with data sources and automation.
• Collaborate with cross-functional teams to meet needs.
• Document policies and data tools for knowledge transfer.
• Foster a culture of dedication, curiosity, and improvement.

Skills

Analytics

Forecasting

Data science

Automation

Python

SQL

Communication

Education

University degree in Engineering/Math/CS/Applied Math/Finance

Tools

Python

dbt

SQL

Airflow

Excel

Job description

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.

About the role:

Do you love diving into data, solving problems with tech, and learning how fintechs get funded by lenders? Are you equally skilled at balancing deep thinking with pragmatic execution, and always delivering on time? 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! We are seeking a Manager of Risk Analytics & Modeling - Forecasting, to work under the direction of the Director - Risk Analytics, Data Science & Reporting to deliver accurate and precise time series models and forecasts that deliver the insights necessary to optimise planning and decision-making. The chosen candidate will also play a key role in building new forecasting capabilities, operationalising and automating forecasting processes, leading forecasting deep dives, and arming stakeholders across the business with the information and advice needed to win. If bouncing between building predictive forecasts, responding to urgent leadership requests, and figuring out how to turn complex human behaviour into succinct algorithms excites you, then you're the dynamic forecasting analytics and modeling manager we're looking for! Just make sure to bring your communication "A-game" along with your drive, personality and aptitude for solving problems. Translating macroeconomic effects and microeconomic personal intermediated decision‑making into accurate and precise predictions is no small feat and requires a ton of team‑based continuous improvement.

What you'll be doing:

• Build and refine accurate unit economic, channel, and borrower‑level vintage and segment risk and valuation models
• Build and refine cashflow and profitability (stock‑flow, time‑series, and econometric) forecasts for consumer & channel partner credit and fraud losses across products, segments, and stakeholders
• Develop, automate, and deliver high‑quality daily, weekly, monthly, quarterly and annual Loss Forecasts and supporting analysis, on time, to Executive and Senior Management
• Go beyond the surface level to build sophisticated yet explainable models that connect data to real‑world events, customer attitudes and behaviors to deliver insights and inform high‑value business decisions
• Continuously improve efficiency by identifying high quality, well‑managed data sources and opportunities to apply automation, data pipelines, and AI to your work
• Partner with cross‑functional teams to understand their needs and goals to proactively ensure they have the models, tools, and insights needed to succeed
• Participate in strategic projects and initiatives related to risk analytics, data science, reporting, strategy and operations
• Document all policies, strategies, data sets, and tools (using tools like Confluence) in ways that ensure clarity and a seamless and accurate internal transfer of knowledge
• Foster a team culture rooted in dedication, curiosity, and continuous improvement.
• Bring energy, positivity, a critical eye, unimpeachable integrity, a team‑first attitude, and a desire to contribute to building something great, together

Who you are:

You bring an engineering mindset and look at forecasting as data science problem that needs to work well in, and adjust to, the real world You have advanced analytics, data engineering, and automation skills, with a knack for translating complex human behaviours into explainable predictions through system mapping, data analysis and financial modelling Elite critical thinking and problem solving, impeccable judgment, and advanced communication (verbal, visual, and written) skills required Legitimately curious and passionate about finding the "right answer" with a detail‑oriented mindset and a "healthy sense of paranoia" Highly organized, disciplined and driven, with the ability to manage competing priorities while meeting deadlines University degree in Engineering, Math, Computer Science, Applied Math or Applied Sciences, Finance, or other quantitative discipline 5+ years of full‑time and/or internship/PEY experience in analytics, data science, strategy, risk management and/or finance, focused on modeling, analytics, and/or forecasting 4+ years of applied experience in building models (Python, Excel), data pipelines (dbt, SQL, Airflow), and/or automating pr