Sub-Nanosecond Precision: HFT Data Scientist Wanted for Latency Analysis and Market Microstructure Research

[Recruiter-Jim]

I'm hiring for the following position in NYC / Chicago / London.​

The Challenge: Deciphering the Market's DNA at the Nanosecond Level​

In the high-frequency trading (HFT) arena, where fortunes shift in the blink of an eye, understanding the intricate dance of market data is paramount. We're seeking a highly specialized data scientist to join the post-trade analysis team, focused on dissecting exchange feeds, optimizing trading strategies in relation to exchange matching logic, and uncovering hidden anomalies to inform the development of cutting-edge FPGA strategies.

Mapping the Dynamic Exchange Landscape:

Exchanges are constantly evolving, introducing new protocols, features, and data feeds. This dynamic landscape, coupled with rapid technological advancements, demands continuous adaptation and optimization of trading strategies.

Your Role Will Involve:

Latency Analysis:

• Pinpointing Bottlenecks: Utilize time series analysis to meticulously examine the timestamps of market data and trading events, identifying latency bottlenecks in the trading infrastructure, such as network delays or slow processing, which can hinder performance and erode profits.
• Identifying Arbitrage Opportunities: Analyze market data across different exchanges and instruments to uncover latency arbitrage opportunities that arise from minute differences in the speed of information dissemination.
• Ensuring Peak Performance: Employ data science techniques to ensure HFT systems operate at peak performance by continuously monitoring key metrics like order execution speed, fill rates, and overall system latency. Build dashboards and visualizations to track performance and alert traders to potential issues.

Anomaly Detection and Algorithmic Enhancement:

• Time Series Analysis and Statistical Modeling: Employ time series analysis and statistical modeling to identify unusual market behavior that deviates from expected patterns, including sudden price spikes, unexpected order flow, or other anomalies that might signal trading opportunities or potential risks.
• Algorithmic Enhancement: Leverage insights from anomaly detection to refine trading algorithms, adapting them to changing market conditions and capitalizing on unusual events. This might involve adjusting trading parameters, incorporating new data sources, or developing entirely new algorithms.

Market Microstructure Research:

• Statistical Modeling: Develop sophisticated statistical models to quantify the extent of market inefficiencies, such as stale quotes and lead-lag relationships, predicting their occurrence and informing trading strategies.
• Network Analysis: Analyze network traffic data to identify sources of latency that contribute to stale quotes, collaborating with network engineers to optimize network infrastructure and minimize delays.
• Market Microstructure Analysis: Delve into the rules and mechanisms of different markets to understand the factors that drive lead-lag relationships, developing trading strategies that exploit these relationships for profit.

In essence, you will empower the firm to:

• Gain a competitive edge: By extracting valuable insights from the vast sea of market data.
• Optimize trading strategies: By identifying and exploiting market inefficiencies.
• Mitigate risks: By detecting anomalies and adapting to changing market conditions.

The Ideal Candidate:

We're looking for an individual with a unique blend of skills and experience:

• Background in ultrafast science: Experience dealing with nano/picosecond measurements, providing a strong foundation for analyzing high-frequency data.
• Data science expertise: Proficiency in NumPy, Pandas, XGBoost, and time series analysis, enabling you to extract meaningful insights from complex datasets.
• Network protocol knowledge: An understanding of TCP/UDP and experience with network programming, crucial for analyzing exchange feeds and optimizing data flow.
• Data visualization skills: Ability to communicate complex data clearly and effectively, facilitating data-driven decision-making.
• Trading firm experience: 2+ years of experience in a quantitative role at an HFT firm is strongly preferred.
• Kaggle enthusiast: A passion for data science competitions, demonstrating your ability to solve complex problems and push the boundaries of analytical techniques.

Join the team in Chicago NYC, or London.