Data Scientist II

Develop scalable analytics solutions using Python, SQL, and PySpark within cloud environments (e.g., Azure Databricks).,Build curated datasets, automated pipelines, and analytics layers that support operational monitoring, performance insights, and regulatory controls.,Analyze large, complex datasets to identify trends, risks, gaps, and optimization opportunities.,Translate ambiguous business questions into structured analytical frameworks and actionable deliverables.,Embed data quality checks, validation, and automation into all analytics products.,Develop and maintain statistical and machine learning models to support fraud detection capabilities or ensure fair banking compliance.,Collaborate with Model Risk Management and other control partners to ensure developed models are effective, stable, and unbiased.,Perform quantitative analysis to identify fair lending risks.,Visualize insights from the data to tell and illustrate stories that clearly convey the meaning of results to decision-makers and stakeholders.

Undergraduate degree or advanced technical degree preferred (e.g., math, physics, engineering, finance, or computer science).,Graduate degree preferred or progressive project work experience.,3+ years of relevant experience; higher degree education and research tenure can be counted (some sources also mention 2+ years of experience in advanced analytics or data science).,Strong organizational skills with the ability to work in a fast-paced environment and manage multiple deadlines and priorities.,Ability to effectively work in teams across the bank with multiple stakeholders and to influence and align others.,Strong risk acumen - challenges the status quo and proactively manages risks.

Bachelor's Degree (Undergraduate degree or advanced technical degree preferred), Graduate Degree preferred.