Senior Data Scientist (5+ years) to advance predictive credit risk modeling using R, Python, an[...]

Our financial services client is seeking a Senior Data Scientist (5+ years) to advance predictive credit risk modeling using R, Python, and machine learning across pricing and underwriting processes. Join a high-performing quantitative research team developing innovative data-driven financial models within a diversified financial organization. This role builds on existing automated loan adjudication initiatives to deliver next-generation predictive modeling and strategic financial insights. The team environment offers direct collaboration with executives and exposure across multiple financial institutions. The position is permanent, based in Edmonton, with an opportunity to impact business-critical investment and lending strategies. Must Haves

Several years in data science applying statistical analysis and predictive modeling Proficiency with R, Python, Stata, MATLAB, or SQL for large-scale analysis Ability to build structured evaluations of data science impact on business outcomes Experience working with real-world financial data and complex processes Undergraduate or graduate degree in data science, statistics, mathematics, or a related field Nice to Have

Experience implementing machine learning-based solutions Previous managerial or team lead experience Competency in data pipeline structuring Background in finance or insurance industries Responsibilities

Develop the next-generation automated loan adjudication system Refine predictive credit risk models and expand business feature sets Investigate current data science opportunities across affiliated financial institutions Research and build models to produce measurable financial gains Bridge analytical results with practical business decisions Collaborate with senior leaders to enable data-driven strategies

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