Company provides comprehensive brokerage, investment and financial services to individual investors globally. Recognized as one of the largest retail brokerage networks in the U.S., Company’s financial representatives cover multiple client segments from affluent to ultra- high net worth. The product range offered to client’s spans mutual funds, equities, fixed income products, alternative investments, separately managed accounts, banking & personal lending, mortgages, insurance and annuities.
The Decision Sciences team goal is to help the organization make fact based and scientifically developed decisions around risk and opportunities, which help drive top and bottom line growth. The incumbent is expected to mine Company’s book of business to identify new or existing customer opportunities for the Private Bank.
The ideal candidate will possess previous predictive modeling experience in a retail consumer banking environment, strong leadership, communication, collaboration and project management skills, a thorough understanding of applied statistics theory as well as have a strong command of Python, SQL and SAS- especially the statistics and optimization packages. Candidate must have significant hands-on experience managing large scale banking projects using banking behavioral internal and external data in advanced analytics projects with ability to influence people across all levels of the organization.
- Develop applied advanced analytic solutions/predictive modeling and optimization to drive bottom line transaction, revenue, new account and retention growth through private bank customer, prospect and advisor behavioral analytics.
- Develop customer segmentation/statistical clustering based solutions using internal behavioral, financial performance and demographic, credit bureau and financial holdings externally purchased data
- Support the development of banking customer engagement, cross sell and new customer acquisition strategies, programs and digital capabilities using contextual insights from applied advanced analytics and predictive modeling tools
- Develop and collaborate to build bank product based artificial intelligence /machine learning-based next best action recommendation systems for Financial Advisors and digital campaign targeting using predictive analytics
- Develop and provide private bank modeling/scoring and advanced analytic effectiveness reporting, measurement and testing strategies /design of experiment approaches and attribution rules
- Run business case capstone/ROI scenarios by establishing initial opportunity sizing estimates, along with preliminary cost and time estimates
- Integrate/interpret primary research data to inform advanced analytic analyses and solutions including predictive modeling
- Support new product development process using predicative analysis based on past performance, market trending and relevant research data points
- Interact with a wide variety of business units within the Private Bank group, build banking intelligent programs by managing components of market exploration and business case initiation, defining appropriate target audiences for strategies, building hypotheses and assumption to test in the marketplace, conducting in partnership research and analysis, developing initial financial projections, and potentially project charter & recommendations.
- Work effectively in cross-functional teams, having demonstrated strong partnerships with both internal and external business partners and alliances
- Demonstrated ability to collect and organize data, work effectively with complex relational databases (Hadoop, Teradata), conduct analysis and report on and apply results to “actionable insights/recommendations”
- Power user of Python, SQL, SAS Base/Stat/Macro and other statistical software packages (R) with Enterprise Miner experience a plus. Minimum 5 years experience with Python & R.
- Strong predictive data modeling experience is required with proven application in applying Decision Trees, Regression analysis, Neural Networks, Clustering and other data mining techniques, experience with time series, experimental design and attribution rules
- Demonstrated ability to transform business needs into technology requirements that both the business and technology understand
- Self-starter with strong and creative problem-solving skills
- Need to be able to succinctly communicate ideas, recommendations orally and in writing to a wide range of audiences, as well as exceptional listening and presentation skills
- 5+ years of consumer banking experience, 3+ years of consumer banking analytics/advanced analytics experience
- 5+ years of direct or cross functional project management requirement
- Master’s degree in quantitative field: MBA, Master of Science or PHD in applied science discipline
- Strong deterministic analytic leadership experience with limited day-to-day direction required by manager