As a Data Science Lead Vice President in Risk Management, you will help build a foundation of state-of-the-art technical and scientific capabilities to support a number of ongoing and planned data analytics projects. We build partnerships with stakeholders in this role to facilitate adoption of the analytical solutions by the lines of business. You will require frequent interaction and communication with cross-functional partners will be visible to the managers and executives of the organization. You will excel at creative thinking and problem solving, be self-motivated, confident and ready to work in a fast-paced energetic environment.
Job responsibilities
- Mentor and guide a highly efficient team, responsible for using advanced Machine Learning techniques to build capabilities for mitigating fraud across various payment channels such as QuickPay, Wires, ACH, Check as well as Digital Account Originations, Credit Card Originations etc.
- Work closely with business analysts, product owners and operations to find tangible opportunities to prevent fraud, enhance customer experience and provide insights which will allow us to assess the risk of portfolio in several dimensions.
- Drive research, design, implementation, and evaluation of machine learning approaches and analytical tools
- Build an in-depth understanding of the problem domain and available data assets
- Perform ad-hoc exploratory statistics and data mining tasks on diverse datasets from small scale to “big data”
- Investigate data visualization and summarization techniques for conveying key findings
- Partner with and communicate findings to stakeholders to help drive the delivery to market
- Provide leadership, coaching and mentoring to a group of fraud data scientists
- Promote a culture of innovative thinking, developing forward-looking solutions by empowering team members
Required qualifications, capabilities, and skills
- Bachelor’s Degree with concentrations in Mathematics, Statistics, Computer Science, Physical Science, Engineering, or other quantitative discipline
- 5+ years of experience in analytics
- Managerial experience in leading teams with a track record of increasing responsibilities.
- Fundamental understanding of probability and statistics and experience in ML algorithm development using large scale data
- Desire to use modern technologies as a disruptive influence for solving large scale business problems
- Strong verbal and written communication– have the ability to present information in concise easily understandable way
Preferred qualifications, capabilities, and skills
- Master’s Degree preferred
- Prior AWS, Python and PySpark experience preferred
- Experience preferably in data science domain, in risk management within Banking Industry
- Understanding of Graph Analytics will be preferred, but not mandatory