Assoc Dir, Risk Analytics & Data Science

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 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 – Risk Analytics Location: Stamford, CT Salary: $170,000 – 190,000 + Generous Bonus, Incredible benefits, and retirement package!Responsibilities: You will Lead the design and development of enterprise-grade deep analytics, exploring and analyze large, complex datasets to identify patterns, trends, and correlations. You will drive collaboration with cross-functional teams to lead efforts to identify improvement opportunities, source data, create analyses, design solutions, and implement change. You will be responsible for developing complex datasets, extracting meaningful insights, deploying predictive models & data driven solutions to optimize portfolio performance and manage risk appetite. This Sr Data Scientist will play a leadership role in advancing the capabilities and maturity of the firm’s Risk Management and Strategic Planning functions. This is a risk analytics and data science role dedicated to successfully managing the firm’s credit and enterprise risk. Optimize firm’s analytical capabilities, data driven decisioning, and overall performance. Drive business results by enhancing the firm’s data continuum including data architecture, data analytics, and data governance and their unique interdependencies. Create useful, timely, and actionable analytical positions based on large structured and unstructured data sets. Ensure analytical positions foster action and inform decisioning to enhance critical business processes and maximize outcomes. Communicate analytical positions, and recommendations to stakeholders through clear and compelling data visualizations, reports, and presentations. Implement automation and streamline processes to optimize the entire data and analytics platform, ensuring efficient throughput and high-performance outcomes. Lead comprehensive initiative to democratize the use of Advanced Analytics tools (such as Python, R, or SQL) and systems across the Risk and Strategic Planning teams. Partner with the Data and Business Intelligence teams on the design, development, implementation, operation, and ongoing support of critical systems and tools. Stay abreast of the latest advancements in data science, machine learning, and analytics technologies. Represent Risk Management and Strategic Planning in Business Intelligence and Data team design discussions, code reviews, and project-related meetings.Requirements: 8+ years’ experience in Data Science or deep analytics in the financial sector Background in Credit Risk analytics and strategy. Proficiency in programming languages such as Python, R, or SQL with SAS experience in data manipulation, statistical analysis, and machine learning. Experience developing and deploying Data Science solutions leveraging components like Azure OpenAI and Azure Notebooks. Understanding of banking / financial services industry business model Excellent communication and collaboration skills, with the ability to distill complex technical concepts into understandable insights for non-technical stakeholders. Strong analytical mindset and understanding of predictive performance models including application, assessment, and validation Strong expertise in data visualization tools such as PowerBI or Tableau. Experience in training colleagues on programming languages/ analytical tools such as Python, R, SQL, and SAS with experience in data manipulation, statistical analysis, and machine learning.