Systematic Algo Trading Strategies - Quantitative Researcher - Vice President

Wells Fargo•New York, NY

54d•Onsite

About The Position

Candidate will have extensive experience in researching, designing, developing, and managing profitable systematic market making algorithms across electronic trading products. The candidate will work closely with adjacent Strat teams, Trading Desks and E-Trading technology teams to lead the continual research and design of systematic liquidity-servicing strategies. This role will focus on providing quantitative research on pricing and risk strategies within a low-latency framework as well as performing extensive customer pricing optimization & analysis. Research will involve discovery of revenue generation signals and strategies leveraging data-driven techniques, analysis of new alpha signal generators, and performing strategy back-testing. Candidates will have the exciting opportunity to be directly involved in a focal growth area.

Requirements

5+ years of Securities Algorithmic Trading experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education
Lead complex initiatives to resolve algorithmic trading using high-frequency trading technology with broad impact
Act as key participant in developing, implementing, and monitoring risk based programs to recommend decisions to buy or sell financial securities on an exchange for Securities Algorithmic Trading
Review and analyze complex formulas, combined with mathematical models and human oversight that require in-depth evaluation of multiple factors including the use of process and rules based algorithms to employ strategies for executing trades
Make decisions in complex and multi-faceted situations requiring understanding of the function, policies, procedures and compliance requirements that influence and lead broader work team to meet deliverables and drive new initiatives
Collaborate and consult with peers, colleagues and mid-level to more experienced managers to resolve issues and achieve goals
This position is subject to FINRA Background Screening Requirements, including successful completion and clearing of a background check. Internal transfers are subject to comply with 17 CFR 240.17f-2 of the Securities Exchange Act of 1934 and FINRA Bylaws, Article III, Section 3, which states that Associated Persons should not be subject to statutory disqualification. Successful candidates must also meet ongoing regulatory requirements including additional screening and are required to report certain incidents.
Specific compliance policies may apply regarding outside activities or personal investing; affected employees will be expected to provide information to the Wells Fargo Personal Account Dealing Team and abide by applicable policy requirements if hired. Information will be shared about expectations during the recruitment process.
Willingness to work on-site in accordance with current office requirements
Ability to work additional hours as needed

Nice To Haves

5+ years' experience in electronic trading, market microstructure, and quantitative models.
Bachelor's degree in quantitative discipline; advanced degree (Master's/PhD) preferred.
Rates/FX experience a plus.
Advanced proficiency in applied statistics, time-series analysis, data mining, and visualization, including modern machine learning and AI techniques.
Advanced proficiency in statistical programming and scripting languages such as Python (Pandas/NumPy/SciPy/scikit-learn), Java and C++ a plus.
Proficiency in tick databases such as KDB/DeepHaven.
Knowledge of high-frequency trading systems, workflows, and communication paradigms (FIX, binary exchange venues).
Experience partnering with technology to develop and architect low-latency infrastructure.
Strong written and verbal communication; ability to synthesize information rapidly.
Ownership mindset with the ability to manage multiple tasks in a fast-paced team environment.

Responsibilities

Partner with business stakeholders to design and implement foundational quantitative analytics and strategies for optimizing execution in electronic trading platforms.
Research, develop, and optimize pricing and risk algorithms within a low-latency environment.
Understand, maintain, and enhance pricing, risk, and signal code built within the algorithmic framework.
Apply statistical inference and machine learning to identify and predict performance and cost drivers.
Produce ad-hoc analysis and visualizations for business partners.
Document back-testing results, references, and monitoring materials for peer review and ongoing performance evaluation.
Conduct deep quantitative research into market microstructure and empirical performance to drive innovation in pricing and risk strategies.
Translate research into production-grade algorithms that facilitates trading decisions.
Ensure system robustness through rigorous back-testing, system controls, and real-time protections.
Continuously refine logic to adapt to evolving market conditions and client-specific needs.
Design and maintain frameworks to manage trading risk and ensure compliance with internal and regulatory standards.
Monitor live algorithm behavior, detect anomalies, respond to incidents, and participate in change management and post-deployment validation.