Institutional Equity Division - Vice President, Quantitative Researcher – Algorithmic Trading (Mumbai)

Company Profile

Morgan Stanley is a leading global financial services firm providing a wide range of investment banking, securities, investment management and wealth management services. The Firm's employees serve clients worldwide including corporations, governments, and individuals from more than 1,200 offices in 43 countries.

As a market leader, the talent and passion of our people is critical to our success.  Together, we share a common set of values rooted in integrity, excellence and strong team ethic.  Morgan Stanley can provide a superior foundation for building a professional career - a place for people to learn, to achieve and grow. A philosophy that balances personal lifestyles, perspectives and needs is an important part of our culture.

Department Profile

From global institutions to hedge funds, investors come to Morgan Stanley for sales, trading, and market-making services in almost every type of financial instrument in all the world’s financial markets. Morgan Stanley professionals use our network and technology to provide liquidity and sophisticated analysis, to manage risk and execute reliably in the fast-changing markets.

Morgan Stanley’s Institutional Equity Division (IED) is a world leader in the origination, distribution and trading of equity, equity-linked and equity-derivative securities. Our broad and deep client relationships, market-leading platform and intellectual insights enable us to be a world-class service provider to our clients for their financing, market access and portfolio management needs.

Morgan Stanley's Equities Quantitative Research (QR) team develops quantitative models, trading strategies and technology that support the Firm's electronic trading business.

We are looking for an experiencedQuantitative Researcher to join the team in Mumbai, focusing on research and development forMorgan Stanley Electronic Trading (MSET)'s algorithmic trading products.

The role will apply techniques and insights fromhigh-frequency trading, market making and electronic market microstructure to improve algorithmic trading performance and execution outcomes. The successful candidate will combine rigorous quantitative research with strong software engineering skills and experience conducting realistic, high-fidelity simulations usingfull-depth, order-level market data.

What You'll Do

• Research and develop quantitative techniques to improve theperformance, execution quality and trading outcomes of MSET's algorithmic trading products.
• Apply concepts fromhigh-frequency trading and market making to algorithmic execution, including short-horizon price prediction, order placement, liquidity capture, fill probability, queue dynamics and adverse selection.
• Analyze large-scalefull-depth order book and order-level (Level 3) market data to understand market behaviour and identify opportunities to improve trading decisions.
• Develop quantitativemodels, signals and features using order flow, liquidity, cross-asset information and other market data to forecast short-horizon market behaviour and improve execution decisions.
• Apply rigorous statistical techniques includingtime-series analysis, statistical inference and predictive modelling to evaluate research hypotheses and identify robust effects.
• Design and implement high-fidelity, event-driven simulations using historical order-level market data to evaluate trading strategies under realistic conditions, including appropriate modelling ofqueue position, fill behaviour, latency and transaction costs.
• Conductcross-asset research, incorporating information from multiple instruments and order books to improve trading decisions and execution performance.
• Develop rigorous methodologies for measuringexecution quality and trading performance, including transaction-cost analysis and evaluation against relevant execution benchmarks, while accounting for latency, market impact, transaction costs, adverse selection and simulation bias.
• Apply appropriateout-of-sample testing and validation methodologies to distinguish robust signals from overfitting and simulation artefacts.
• Translate successful research into high-performance implementations suitable for latency-sensitive production environments.
• Profile and optimize performance-critical code for latency, throughput and computational efficiency.
• Work closely with quantitative researchers, electronic traders and technology teams globally to take research from hypothesis and simulation through to production.

Qualifications

• 3+ years of professional quantitative R&D experience in high-frequency trading, electronic market making, algorithmic trading or a closely related systematic trading environment.
• Experience applyingmarket microstructure concepts to real-world trading problems.
• Strong programming skills in a performant, low-latency language such asC++, Java or Rust, including experience developing efficient, performance-critical software.
• Strong proficiency inPython or a comparable quantitative research environment for data analysis, modelling and rapid research iteration.
• Experience working withfull-depth / Level 3 order book data and order-level market events, including analysis of detailed order-book state and dynamics.
• Experience developing or usingevent-driven market simulation and backtesting frameworks for high-frequency trading or execution research.
• Strong quantitative and statistical modelling skills, including experience withtime-series analysis, statistical inference, predictive modelling and empirical research.
• Experience designing rigorous experiments and applyingout-of-sample validation to evaluate predictive signals and guard against overfitting.
• Degree inComputer Science, Mathematics, Statistics, Physics, Engineering, Financial Engineering or another highly quantitative discipline.

Preferred Qualifications

• Experience researchingalgorithmic execution, smart order placement, liquidity capture, execution optimization or transaction-cost analysis.
• Experience applying techniques developed in anHFT or electronic market-making environment to broader algorithmic trading problems.
• Strong understanding of electronic market microstructure, includingorder-book dynamics, matching mechanics, queue position, liquidity, fill behaviour, adverse selection and market impact.
• Experience developing and evaluating quantitative trading strategies usingcross-asset and cross-instrument information.
• Strong knowledge of modern C++, algorithms, memory management, concurrency and performance optimization.
• Experience working with very large event-level datasets and high-performance simulation or research infrastructure.

The Candidate

The ideal candidate combines the mindset of aquantitative researcher with strong software engineering ability. They will bring a deep understanding of how electronic markets behave at the order-book level and be able to translate that understanding into practical improvements in algorithmic trading.

We are particularly interested in candidates who can apply the sophisticated modelling, forecasting and simulation techniques used in high-frequency and market-making environments toimprove execution decisions, trading performance and client outcomes across Morgan Stanley's electronic trading platform.

WHAT YOU CAN EXPECT FROM MORGAN STANLEY:

At Morgan Stanley, we raise, manage and allocate capital for our clients – helping them reach their goals. We do it in a way that’s differentiated – and we’ve done that for 90 years.  Our values - putting clients first, doing the right thing, leading with exceptional ideas, committing to diversity and inclusion, and giving back - aren’t just beliefs, they guide the decisions we make every day to do what's best for our clients, communities and more than 80,000 employees in 1,200 offices across 42 countries. At Morgan Stanley, you’ll find an opportunity to work alongside the best and the brightest, in an environment where you are supported and empowered. Our teams are relentless collaborators and creative thinkers, fueled by their diverse backgrounds and experiences. We are proud to support our employees and their families at every point along their work-life journey, offering some of the most attractive and comprehensive employee benefits and perks in the industry. There’s also ample opportunity to move about the business for those who show passion and grit in their work.

To learn more about our offices across the globe, please copy and paste https://www.morganstanley.com/about-us/global-offices​ into your browser.

Morgan Stanley is an equal opportunity employer committed to building and maintaining a workforce that is diverse in experience and background.  Our recruiting efforts reflect our strong commitment to a culture of inclusion, where individuals are hired, developed, and advanced based on their skills and talents.

Our workforce reflects a broad cross-section of the global communities in which we operate, bringing a variety of backgrounds, talents, perspectives, and experiences.

For more information, please visit:https://www.morganstanley.com/people-opportunities/eeo.