Job Description

Are you an experienced Data Scientist with specific experience working with Financial Data, specifically in Credit Risk Analytics, this opportunity is for you!

Exciting Senior Level Data Scientist opportunity with a well know, rapidly growing Commercial Finance leader. This is credit risk analytics and data science role dedicated to successfully managing the firm’s credit and enterprise risk. You will use cutting edge statistical analysis, and machine learning to explore and analyze large complex datasets to identify patterns, trends, and correlations. Competitive compensation, tremendous benefit package and 401k. Cutting edge technology, incredible culture and working environment!

Employee testimonials:

• Fantastic Place to Work. Hope to finish out the rest of my career with this great company!
• Good salary and package deal Friendly environment Great career advancement Everyone loves working here and you feel it!
• Great company, culture, and work-life balance!

Title: Sr Data Scientist – Credit Risk Analytics

Location: Stamford, CT

Salary: $170,000 – $190,000 +Bonus, Incredible benefits, and retirement package!

Key Responsibilities

• Lead advanced analytics to identify patterns, trends, and correlations in large, complex financial datasets.
• Develop and deploy predictive models to optimize credit risk management and portfolio performance.
• Enhance data architecture, analytics, and governance to improve decision-making and business outcomes.
• Automate and streamline data processes for efficiency and high-performance outcomes.
• Communicate insights effectively using data visualization tools (PowerBI, Tableau) for actionable decision-making.
• Collaborate with cross-functional teams to identify opportunities, design solutions, and implement changes.
• Drive adoption of advanced analytics tools (Python, R, SQL) across Risk and Strategic Planning teams.

Key Qualifications

• 5+ years of experience in data science and deep analytics within financial services, specifically credit risk analytics.
• Expertise in credit risk strategy , predictive modeling, and portfolio optimization.
• Advanced proficiency in Python, R, SQL, and SAS for data manipulation, statistical analysis, and machine learning.
• Strong understanding of banking industry models and financial risk assessment.
• Experience deploying data science solutions leveraging Azure OpenAI and Azure Notebooks.
• Exceptional communication skills to translate technical insights for non-technical stakeholders.
• Expert in data visualization tools (PowerBI, Tableau) for impactful reporting.

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