Vice President, Data Management & Quantitative Analysis- Quant Developer

Vice President, Data Management & Quantitative Analysis-

Quant Developer

At BNY, our culture empowers you to grow and succeed. As a leading global financial services company at the center of the world’s financial system we touch nearly 20% of the world’s investible assets. Every day around the globe, our 50,000+ employees bring the power of their perspective to the table to create solutions with our clients that benefit businesses, communities and people everywhere.    

We continue to be a leader in the industry, awarded as a top home for innovators and for creating an inclusive workplace. Through our unique ideas and talents, together we help make money work for the world. This is what #LifeAtBNY is all about.

We’re seeking a future team member for the role of Vice President, Data Management & Quantitative Analysis-

Quant Developer

to join our

Margin Methodology Development and Backtesting

team. This role is located in Pune and will be working in a hybrid capacity. (Currently 4 days a week in the office).

In this role, you’ll make an impact in the following ways: 

We are seeking a

Quant Developer

with strong experience in

margin methodology development, backtesting, and model validation support

, with primary focus on

Securities Finance businesses

, including

Prime Services, Repo, Securities Lending, Clearing, and Wealth Solutions

.

This role will focus on building and enhancing analytics and tooling to support the

design, implementation, backtesting, review, and approval

of margin methodologies across these businesses. The ideal candidate will have experience in

Historical VaR

,

stress testing

, and

dynamic margin frameworks

, including

Rules-Based Dynamic Margin

and

Stress-Based Dynamic Margin

methodologies.

The successful candidate will combine strong

quantitative modeling expertise

,

hands-on Python/C++ development capability

, and practical understanding of

margining use cases relevant to financing, collateralized products, and client risk management

.

 

• Develop, maintain, and support

Python/C++ quantitative libraries and analytical tools

for

margin methodology development

,

backtesting

, and

stress testing

across

Securities Finance businesses

, including

Prime Services, Repo, Securities Lending, Clearing, and Wealth Solutions

.

• Design and implement robust

backtesting frameworks

for margin models using

historical simulation

,

Historical VaR

, and

stress-based techniques

.

• Support the development, enhancement, and performance assessment of

Rules-Based Dynamic Margin

and

Stress-Based Dynamic Margin

methodologies.

• Perform quantitative analysis on margin model outcomes, including

coverage testing

,

procyclicality assessment

,

sensitivity analysis

, and

ongoing model performance monitoring

.

• Analyze historical market data and stress periods to assess margin model behavior under both normal and stressed market environments relevant to

financing and collateralized trading businesses

.

• Work closely with quantitative analytics, risk, model governance, business stakeholders, and technology teams to support the

model review, validation, and approval process

.

• Prepare quantitative evidence, documentation, and supporting analytics for

internal governance

, model oversight, and regulatory or control reviews.

• Investigate issues related to market data, scenario generation, backtesting exceptions, and margin model performance.

• Partner with platform engineering and technology teams to integrate margin analytics and backtesting tools into enterprise risk and margin systems.

Contribute to

AI-enabled quantitative workflow solutions

where relevant for analytics, monitoring, controls, and reporting.

To be successful in this role, we’re seeking the following: 

• Bachelor’s or Master’s degree in a relevant technical discipline such as

Computer Science, Mathematics, Statistics, Financial Engineering, Physics, or another quantitative field

.

• Strong programming skills in

Python

and/or

C++

, with proven experience building quantitative analytics libraries, risk tools, or backtesting engines.

• Strong understanding of

margin methodologies

,

model backtesting

,

Historical VaR

, and

stress testing techniques

.

• Experience with

Rules-Based Dynamic Margin

and/or

Stress-Based Dynamic Margin

methodology development, calibration, backtesting, or performance assessment.

• Good understanding of margining concepts relevant to

Securities Finance

, including businesses such as

Prime Services, Repo, Securities Lending, Clearing, and Wealth Solutions

.

• Familiarity with

model governance

,

validation expectations

, and

approval processes

for quantitative methodologies.

• Strong knowledge of

market risk concepts

, including

VaR

,

stress testing

,

scenario analysis

,

sensitivities

, and

tail-risk evaluation

.

• Experience working with

historical market data

, scenario construction, and quantitative model performance analysis.

• Strong analytical and problem-solving skills with the ability to interpret model behavior and communicate findings effectively.

• Good understanding of software engineering principles, including

object-oriented design

, testing, code quality, and maintainable development practices.

• Strong communication and collaboration skills, with the ability to work across quantitative, business, risk, governance, and engineering teams.

 

Preferred Qualifications

• Experience supporting margin methodologies in

Securities Finance

businesses, especially

Prime Services, Repo, Securities Lending, Clearing, and Wealth Solutions

.

• Experience in

securities financing, clearing, exchange, CCP, derivatives margin, counterparty risk, or market risk

environments.

• Exposure to

margin model validation

,

regulatory review

, or

quantitative model governance

processes.

• Knowledge of

fixed income, equities, FX, and financing products

, particularly from a

risk, collateral, and margining perspective

.

• Familiarity with

procyclicality controls

,

margin coverage standards

, and

stress calibration practices

.

• Experience in quantitative development, model development, or risk analytics roles within

investment banks, clearing houses, exchanges, broker-dealers, or other financial market infrastructure institutions

.

 

Ideal Candidate Profile

• Hands-on Quant Developer with strong experience in

risk and margin analytics

• Deep interest in

margin methodologies for Securities Finance businesses

• Proven capability in

backtesting quantitative methodologies using historical market data

• Comfortable operating in environments involving

model governance, validation, and approval

• Able to bridge

quantitative research

,

model implementation

, and

production-grade analytics tooling

• Experience supporting

dynamic margin frameworks

for

Prime Services, Repo, Securities Lending, Clearing, or Wealth Solutions

is highly desirable

At BNY, our culture speaks for itself, check out the latest BNY news at:

https://www.bny.com/corporate/global/en/about-us/newsroom.html BNY Newsroom

https://www.linkedin.com/company/bnyglobal/posts/?feedView=all BNY LinkedIn 

 

 Here’s a few of our recent awards: 

• America’s Most Innovative Companies, Fortune, 2025

• World’s Most Admired Companies, Fortune 2025

• “Most Just Companies”, Just Capital and CNBC, 2025

Our Benefits and Rewards:

BNY offers highly competitive compensation, benefits, and wellbeing programs rooted in a strong culture of excellence and our pay-for-performance philosophy. We provide access to flexible global resources and tools for your life’s journey. Focus on your health, foster your personal resilience, and reach your financial goals as a valued member of our team, along with generous paid leaves, including paid volunteer time, that can support you and your family through moments that matter. 

 

BNY is an Equal Employment Opportunity/Affirmative Action Employer - Underrepresented racial and ethnic groups/Females/Individuals with Disabilities/Protected Veterans.