About the role

Senior Data Analyst in Risk Business Intelligence, enhancing credit decisioning in a fast-growing fintech company. Collaborating on analytics, data engineering, and strategic recommendations.

Responsibilities

Architect and guide the delivery of scalable, reliable data pipelines and analytical workflows supporting credit risk use cases across AWS and Snowflake.
Create advanced dashboards and reporting in Tableau, Hex, Power BI, or Qlik Sense for executive visibility and operational monitoring.
Analyze credit bureau data, market trends, and internal portfolio performance to surface insights that influence underwriting, pricing, and collections strategy.
Lead analytical projects from scoping through delivery, translating complex questions into structured frameworks and actionable recommendations.
Modernize legacy data flows, unify batch and streaming sources, and improve data models to support self-serve analytics and ML initiatives.
Collaborate with engineering, analytics, product, and finance teams to clarify ambiguous problems, assess risks, and propose scalable solutions.
Use Python and AI tools to perform advanced exploratory analysis, build predictive insights, and validate statistical outputs.
Partner with ML and Finance teams to ensure datasets meet the appropriate latency, accuracy, and governance standards.
Present findings and strategic recommendations to senior leadership, influencing direction and decisions across credit and product lines.
Mentor analysts and contribute to elevating Spring’s analytical rigor, documentation standards, and data-driven culture.

Proven experience in data analytics with exposure to credit risk, consumer lending, fintech, banking, or financial-services analytics.
Strong proficiency in SQL and Python for analytical workflows, modeling, and exploration.
Advanced skills in BI tools such as Tableau, Hex, Power BI, or Qlik Sense, with experience creating reports for senior management.
Experience working with cloud data platforms such as Snowflake and AWS.
Strong understanding of data modeling, schema evolution, and how pipeline design impacts downstream analytics.
Ability to independently lead cross-functional initiatives and align analytical work with business value.
Excellent communication skills and the ability to present insights clearly to senior stakeholders.
Comfort using AI tools to accelerate analysis, forecasting, segmentation, and hypothesis generation with appropriate validation.
Experience partnering with data engineering, BI engineering, and product teams on data requirements, pipeline improvements, and quality assurance.
Experience documenting dashboards, metric definitions, and analytical logic to support transparency and adoption.

Comprehensive benefits package, including extended health, dental, and vision coverage — with 100% of monthly premiums covered by the Spring.
GRSP matching program to support your long-term financial goals.
Transit-Friendly Employer (Transit allowance).
A modern, collaborative workspace in the heart of downtown Vancouver.
Ongoing career growth opportunities