Lead-Quantitative-Analytics-Associate---Finance & Treasury

ABOUT THE JOB

The Lead Quantitative Analytics Associate - Finance is primarily responsible for using advanced mathematical techniques to develop predictive time-series models related to Pre-Provision Net Revenue (PPNR) for internal stress testing, Comprehensive Capital Analysis and Review (CCAR) stress testing, and the corporate forecast.  The role may also support quantitative process related to Interest-Rate Risk (IRR) for Asset-Liability Management (ALM) and Liquidity Risk.  The ideal candidate will be able to translate a strong banking acumen into robust quantitative processes.  Success factors include: designing advanced modeling approaches and developing / modifying existing models to meet changing business needs or in response to trends and strategy; exercising functional knowledge in analytical programming languages, data literacy, and model development to deliver predictive analysis to inform business problems; leading conversation with partners, delivering the right message and translating complex theories and ideas into easy-to-understand language; and serving as an emerging leader and role model across team.

ESSENTIAL JOB FUNCTIONS

• Use critical thinking to develop insights and deliver predictive analysis that answers business problems related to “what will happen next?”
• Develop, design, and/or leverage advanced modeling approaches, standard techniques for data inference and performance, and algorithms / models.
• Identify and anticipate business need; obtain the right information
• Develop robust quantitative processes that will withstand the test of time.
• Deliver the right message to partners using past trends to predict future behavior and linking conclusions based on analyses to business impact.
• Navigate model approval process as needed
• Make process improvement suggestions
• Be an emerging leader across the team: Serve as a role model to others; provide input to work product of junior staff; Help others to develop, publish, and customize models
• Identify and employ best practices.

REQUIRED QUALIFICATIONS

• Master’s degree in economics, statistics, mathematics, financial engineering, data sciences, predictive modeling, or other quantitative disciplines or equivalent experience; minimum of 2 years of relevant experience.
• Bachelor’s degree or equivalent experience in economics, statistics, mathematics, financial engineering, data sciences, predictive modeling, or other quantitative disciplines; minimum 5 years of relevant experience.

IDEAL CANDIDATE

• Have a robust understanding of Finance and Accounting concepts.
• Minimum of 5 years experience in PPNR modeling for a Category IV (or higher) bank
• Ability to identify downstream model impacts on related processes.
• Intuition on the broader macroeconomic impact on the bank’s balance sheet

DATA LITERACY

• Working knowledge of:
  • Different types of data and techniques for managing these data structures
• Ability to:
  • Assist / guide others in information retention, coordination with data stewards, and anticipation of process/procedure needs
  • Link conclusions based on data analysis to business impacts
  • Define processes for integrating and repurposing data analyses

TECHNOLOGY & TECHNIQUES

• Advanced Microsoft Office Suite
• SQL/NoSQL
  • Relationship data structure
  • Selecting and retrieving data including unstructured data retrieval, archival, and ETL
  • Databases
• Advanced Python/R/SAS:
  • Databases
  • Efficient coding
  • Can build strong code controls and translate code into high-level commentary
• Understanding of and ability to leverage:
  • Cloud-based computing
  • Distributed computing

MODEL BUILDING & MAINTENANCE

• Moderate-to-strong competency in time-series forecasting techniques.
  • Ability to detect and mitigate time-series forecasting issues that would not appear in backtesting (e.g., overfitting)
• Understands and can leverage:
  • Optimization techniques and supporting numerical analysis requirements in algorithms / models
• Ability to:
  • Interpret performance and reliability of assumptions; identify when to escalate
  • Leverage and lead the design of advanced modeling approaches
  • Develop / design standard techniques for data inference and performance perspectives
  • Determine use requirements based on business processes
  • Identify and employ best practices in implementation.

EXPECTED COMPETENCIES

• Leadership: Emerging leader across team; Role model to others – may coach and develop; Provides direction/mentorship to junior staff
• Partnering / Influencing: Proven relationship building ability; Strong interpersonal skills; Can lead the conversation with partners in the business, technology, etc.; Sought out to by business partners and team members; May coach and develop relationship building skills in others; Developing comfort with influencing and consulting typically with mid-level leaders

• Business Acumen: General understanding of finance and accounting concepts related to standard financial reports such as the balance sheet and income statement.  Understands LOB strategy; Knows our competition and industry; Possesses intellectual curiosity; Understands key drivers of financial results and business impact; Aware of the competitive environment.

• Critical Thinking / Problem Solving: Leverages critical thinking and business acumen to provide solutions to increasingly more complex problems; Understands impacts / intersections with other business partners / LOBs; Aware of potential pitfalls with each recommended solution; thoroughly vets and thinks through options before making a decision.
• Communication: Strong writing skills; organizes material for brevity, persuasiveness, and impact; Effectively communicates key points to respective stakeholders, with the right amount of detail; Proactively shares information beyond those at the table who may have a need to know; Comfortable in situations where conflict is present; Demonstrated presentation development and delivery skills; Ability to create presentations that include the right data / information and tell the right story.