Senior Quantitative Analyst (Stress Testing Model Development) - SAS/Python

TD; Wilmington (DE); In loco; USD 76.000 - 114.000; Tempo pieno

Descrizione del lavoro

TD Bank in Wilmington, Delaware is seeking a Senior Quantitative Analyst to join the treasury model development team. You will develop quantitative models to forecast balance and fee income for loan and deposit products, working in-office in Wilmington, DE or Mount Laurel, NJ.

Ideal candidates have a master's in a quantitative field, hands-on experience with SQL/SAS/Python/R, and strong ability to communicate complex concepts to business partners and regulators.

Competenze

• Master's degrees in statistics/math/econometrics/engineering; PhD preferred but not required.
• 0 to 1 year of experience in developing Quantitative Models (CCAR/PPNR/DFAST modeling experience a big plus).
• Strong hands-on expertise with SQL/SAS/Python/R.

Mansioni

• Provide financial, analytical modeling for business projects.
• Conduct complex quantitative analysis for transactions and products.
• Develop advanced quantitative models to enable pricing and risk management.

Conoscenze

Quantitative modeling

Strong communication

Cross-functional collaboration

Formazione

Master's in quantitative field

PhD preferred

Strumenti

SQL

SAS

Python

R

Descrizione del lavoro

Work Location

Wilmington, Delaware, United States of America

Hours

40

Pay Details

$76,290 - $114,440 USD

TD is committed to providing fair and equitable compensation opportunities to all colleagues. Growth opportunities and skill development are defining features of the colleague experience at TD. Our compensation policies and practices have been designed to allow colleagues to progress through the salary range over time as they progress in their role. The base pay actually offered may vary based upon the candidate's skills and experience, job-related knowledge, geographic location, and other specific business and organizational needs.

As a candidate, you are encouraged to ask compensation related questions and have an open dialogue with your recruiter who can provide you more specific details for this role.

Line of Business

Risk Management

Job Description

Position Overview

This position will support TD Bank's treasury model development team in developing quantitative models to forecast balance and fee income for various loan and deposit products. (Note: this is an in-office position in our Wilmington, DE or Mount Laurel, NJ office; "NOT" Remote eligible)

Preferred Qualifications

• Quantitative academic background: Master's degrees in statistics/math, econometrics, engineering, etc. (PhD preferred but not required)
• 0 to 1 year of experience in developing Quantitative Models (CCAR/PPNR/DFAST modeling experience for Stress Testing is a big plus).
• Strong hands‑on expertise with SQL/SAS/Python/R.
• Deep knowledge in banking business and familiar with the banking industry data.
• Proven ability to communicate complex technical concepts to business partners, senior leadership, and regulators.
• Proven experience working effectively in cross functional environments, collaborating across business, risk, technology, and compliance teams.

The Senior Quantitative Analyst provides the quantitative analysis and builds the advanced quantitative models to meet business requirements. In addition, the Senior Quantitative Analyst provides highly specialized quantitative analytical and modeling support at the assigned line(s) of business and Develop advanced quantitative models to enable pricing of products. Provide highly specialized analytical and modeling support for these models including optimal pricing and risk management.

Depth & Scope

• Provides financial, analytical, modeling expertise to build quantitative models for business projects
• Conducts complex quantitative analysis as it applies to areas of responsibility, generally aligned to specific transactions and products
• Performs statistical model assumptions' tests for soundness of model theory
• Hands on coding and building of quantitative models
• Reviews model results and identifies unexpected results
• May develop specialized analytical tools for projects or ongoing use
• May develop conclusions and courses of action to rectify discrepancies as well as analyses
• Develops and analyzes key metric and plan variances and related information
• Develops analyses of performance and predictive data
• Compiles and generates ad‑hoc analytical reports
• May lead additional research efforts, applying expertise in statistical analysis and modeling
• Explores the best practice modeling techniques for model enhancement
• Highly seasoned professional role requiring substantial knowledge / expertise in a complex field and knowledge of broader related areas
• Integrates knowledge of the enterprise sub‑function’s or business line’s overarching strategy in developing solutions across multiple functions or operations
• Interprets internal/external business challenges and the industry environment, recommends course of action and best practices to improve products, processes or services
• Acts as a technical expert / lead integrating cross‑function understanding within their own field of specialty; may manage team(s) of related specialists
• Leads cross‑functional teams or projects with significant resource requirements, risk and / or complexity
• Independently manages end‑to‑end functional programs
• Solves or may lead others to solve complex problems; leads efforts or partners with others to develop new solutions
• Uses sophisticated analytical thought to exercise judgement and identify solutions
• Impacts the achievement of sub‑function or business line objectives within the area they are accountable for
• Work is guided by policies and industry standards/methods
• Communicates difficult concepts; converts information to compelling business context and advice; influences and gains alignment across increasingly senior stakeholders
• Works autonomously as the lead and guides others within area of expertise
• Independently handles all but the most complex and unusual issues

Education & Experience

• Undergraduate degree required, advanced technical degree preferred (e.g., math, physics, engineering, finance or computer science) Graduate's degree preferred with either progressive project work experience or
• 3+ years relevant experience, In‑depth knowledge of quantitative models and statistical analysis
• Ability to effectively interpret, select appropriate techniques, take independent action, communicate, and follow‑through
• Strong communications skills, both written and verbal
• Strong interpersonal and consultative communication skills with well‑developed presentation skills
• Ability to manage competing priorities effectively, making good decisions based on business priorities and objectives
• Practical knowledge of financial analysis techniques and methodologies
• Ability to employ complex analytical tools and statistics to perform analysis and forecasting of financial and other business information
• Proficiently use Microsoft Office tools to prepare and present analysis results to the audience
• Advanced skills in SAS and SQL
• Advanced level in statistical analysis and modeling tools
• Ability to exercise sound judgment in making decisions
• Ability to analyze complex information and develop plans to address identified issues
• Demonstrated skills in conflict resolution, strong intuitive judgment and negotiation/influencing skills, flexibility and adaptability to changing priorities in a fast‑paced environment, along with a strong consultative approach
• Skill in collecting, organizing and analyzing complex or technical data
• Skill in using logic and reasoning to identify the strengths and weaknesses of alternative situations, conclusions or approaches to problems
• Skill in active learning by understanding the implications of new information for both current and future problem solving and decision making
• Skill in identifying complex problems and reviewing related information to develop and evaluate options and implement solutions
• Skill in decision making by considering relative costs and benefits of potential actions and choosing the most appropriate option