Electronic Trading Quantitative Analyst

UBS•New York, NY

9d•$145,000 - $172,500•Onsite

About The Position

We are looking for a Quantitative Analyst to join the Quantitative Analysis & Development team in New York. This role involves performing research, analyzing data, and coding improvements to complex algorithmic trading strategies. The successful candidate will analyze, adapt, and improve the quantitative performance of UBS’s suite of agency algorithmic trading and smart order routing strategies. The team provides execution trading algorithms, smart order routing (SOR), and direct market access products for global clients across Cash Equities, ETD, and FX asset classes.

Requirements

Ideally 2+ years of experience with Algorithmic Trading Strategies, Smart Order Routing and Data Analysis for single stock and portfolio trading.
Proven background in quantitative analysis and development with a degree in Computer Science, Mathematics, Engineering or related discipline (PhD preferred but not a pre-requisite).
Working knowledge of Java (other languages considered).
Proficient in data analysis using statistical software packages such as Python or equivalent.
Experience analyzing tick series market data via KDB / Onetick and extracting data via e.g. SQL.
Proficient with visualization tools such as Tableau or Power BI.
Strong written and verbal communication skills in English to produce comprehensive business requirement specification and model risk documents.
You’re curious to explore how AI can improve how we build, deliver, and optimize workflows. You do this with sound judgment – validating outputs and aligning with policies, risk standards, and ethical use.

Nice To Haves

Knowledge of US cash equity market microstructure with an understanding of low latency trading strategies preferred but not essential.
Knowledge of L3 market data and orderbook mechanics also a plus.

Responsibilities

Perform thorough research on areas such as market microstructure and market impact analysis.
Perform Transaction Costs Analysis (TCA) to minimize executions costs.
Improve consistency of algo performance and reduce outliers and risk, particularly during significant unscheduled as well as scheduled events e.g. index rebalance events.
Design and spec new trading strategies with a particular focus on low latency trading strategies.
Analyze trading patterns and trends within market data (L2 or L3 format).
Employ modern data analytical tools such as machine learning in a controlled and practical way.
Adapt algorithms to adjust to new markets, venues, order types, asset classes and regulation.
Generate intraday trading signals and volume forecasts from microseconds to minutes.
Communicate with internal stakeholders and external clients and vendors to understand business requirements and market trends.
Produce analytics and reports to monitor and benchmark trading performance both internally and for clients.