Quantitative Analytics Associate

Quant Analytics - Associate

Advance your career in Quantitative Analytics with a leading role at the world’s most innovative bank, renowned for valuing creativity and excellence. The Finance Decision Optimization product team within Consumer and Community Banking Finance is tasked with overseeing all analytics and support related to the development, maintenance, and production deployment of AI/ML-based models across all Consumer and Community Banking Lines of Business. If you are a strategic thinker with a passion for promoting solutions in quantitative analytics, you have found the right team.

 

As a Quantitative Analytics Professional within our Consumer and Community Banking Finance team, you will play a crucial role in defining, refining, and achieving the firm’s strategic goals. You will lead analytical initiatives during the Finance Decision Optimization product development for consumer lending products as a part of the Consumer and Community Banking Product and Transformation team. The Finance Decision Optimization team supports various lines of business, including home lending, retail banking, auto finance, wealth management, and business banking. This position requires a visionary approach, the ability to present to executive stakeholders, and the responsibility to ensure engineering teams meet overarching delivery objectives. While this is not a model development role, it involves close collaboration with modeling, data, business, and technology teams to deliver analytical solutions, conduct deep dives, assess whether models under development meet business requirements, and perform back-testing.

 

Job responsibilities - 

• Define modeling requirements for optimizing financial decisions across lending and deposit products, including mortgage, auto, card, business banking, and wealth management.
• Collaborate closely with the business modeling team to develop robust financial decision-making models.
• Present results and recommendations clearly and concisely and curate presentations as per executive audience like CFOs. Work with Modelling & Tech team to conduct tie-out excercise before handing over the models to Tech. 
• Analyze model inputs and outputs to support model development and deployment.
• Collaborate effectively with finance, modeling, data, technology, and business teams.
• Partner with business teams to integrate model outputs into business strategies.
• Conduct comprehensive analyses to assist management in understanding the business impact of financial strategies before and after the incorporation of these models.
• Collaborate with other partners and provide analytical/data support to legal, compliance, Data Governance, Model Review Group, Fair Lending, etc in order for MVP to be released
• Design Minimum Viable Product (MVP) test plans, effectively conduct tests and collaborate with partners to get MVP on release track based on tests results
• Develop and maintain dashboards and relevant reporting to monitor model performance.

 

Required Qualifications, Capabilities, and Skills -

• A postgraduate degree in a quantitative discipline such as Mathematics, Finance, Statistics, Economics, or equivalent work/training is required
• 3+ years of experience in data analytics with a proven track record of increasing responsibility.
• Banking experience in one or more U.S. consumer credit portfolios (e.g., U.S. Mortgage, Home Equity, Credit Card, Automotive, Lease, Business Banking).
• Knowledge of finance processes, particularly pricing and macroeconomics. Ability to synthesize data and communicate effectively to leadership both verbally and in writing.
• Meticulous attention to detail, analytical and inquisitive, with high standards for quality and accuracy.
  Experience with data extraction and analysis tools such as SQL, Python and working experience in public cloud, Databricks
• Proficiency in Microsoft Office, especially Excel and PowerPoint. Strong communication and interpersonal skills, ability to interact with individuals across departments / functions and with senior-level individuals 
• Able to work effectively under pressure and in a rapidly changing environment in order to meet deadlines
• Collaborative, team-oriented, passionate about supporting our internal / external clients
• Self-starter, able to take the initiative and operate independently on a daily basis. Exhibited leadership and desire to oversee the development of junior team members

 Preferred qualifications, capabilities, and skills 

• An advanced degree is preferred.
• Strong technical and statistical skills, with experience in the development or use of ML models preferred.
• Experience with data extraction and analysis tools such as SQL, Python and working experience in public cloud (preferably AWS), Databricks

Experience Level

Mid Level