Quantitative Developer, Systematic Equities.

Millennium Management; Dubai; On-site; USD 80,000 - 150,000; Full time

Job summary

An established industry player is seeking a skilled Quantitative Developer to enhance their systematic equities trading platform. This role involves collaborating with senior management to develop a backtesting and trading system that leverages advanced technology and data analytics. You will be at the forefront of creating visualization tools, ensuring system reliability, and mentoring junior developers. If you are passionate about algorithmic trading and thrive in a dynamic environment, this opportunity offers a chance to make a significant impact in a leading hedge fund known for its innovative approach to market strategies.

Qualifications

• 3-5+ years in algorithmic trading systems development, especially in systematic equity trading.
• Expertise in KDB/Q and Python with experience in data science tools.

Responsibilities

• Collaborate to implement and enhance a systematic equity backtester tool.
• Design and implement trading systems ensuring reliability and scalability.

Skills

KDB / Q

Python

Data Science Tools (Jupyter, pandas, numpy, sklearn)

Quantitative Analysis

Mathematical Modelling

Statistics

Regression

Probability Theory

Software Development Methodologies

Analytical Skills

Education

Bachelor's degree in Computer Science

Master's degree in Mathematics

Degree in Statistics

Tools

Slurm

MOSEK

Job description

Quantitative Developer, Systematic Equities

Job Description : Quantitative Developer, Systematic Equities

Millennium is a top tier global hedge fund with a strong commitment to leveraging market innovations in technology and data to deliver high-quality returns.

We are seeking a quantitative developer to partner with the Senior Portfolio Manager in developing a systematic backtesting, visualization / analyzing, and trading platform for global equity strategies.

Location: London or Dubai preferred

Responsibilities:

1. Collaborate with the Senior Portfolio Manager and other team members to implement and improve an efficient systematic equity backtester tool used for both simulation and live trading.
2. Create visualization and analyzing tools for the input and output of the backtest.
3. Design and implement trading systems, ensuring reliability, scalability, and timely execution.
4. Develop, optimize, and maintain software applications for larger scale equity trading.
5. Work closely with the infrastructure team to connect trading strategies to the firm’s trading infrastructure and connectivity.
6. Conduct thorough testing and debugging of software components, resolving any issues or discrepancies.
7. Work with and centralize multiple vendor data sets.
8. Stay up-to-date with the latest developments in technology and trading practices to continuously enhance systems.
9. Provide technical support and mentorship to junior developers, promoting best practices and knowledge sharing.

Preferred Technical Skills:

1. Expert in KDB / Q and Python.
2. Proficient in modern data science tools stacks (Jupyter, pandas, numpy, sklearn) with machine learning experience.
3. Good understanding of using Slurm or similar parallel computing tools.
4. Bachelor's or Master's degree in Computer Science, Mathematics, Statistics, or related STEM field from a top-ranked University.
5. Proficient in quantitative analysis, mathematical modelling, statistics, regression, and probability theory.
6. Proficient in professional software development methodologies, version control systems, unit testing and debugging tools, and micro-services architecture.
7. Deep understanding of financial markets, including equity markings, corporate actions, hedging.
8. Excellent communication, problem-solving, and analytical skills, with the ability to quickly understand and apply complex concepts.

Preferred Experience:

1. 3-5+ years of experience in algorithmic trading systems development, preferably in systematic equity trading markets.
2. Experience building analytic tools using KDB.
3. Experience using tools, such as MOSEK, for systematic equity hedging and optimizing.
4. Experience working with and centralizing multiple vendor data sets.
5. Experience analyzing metrics for performance and risks for systematic equity trading.
6. Experience collaborating effectively with cross-functional teams, multitasking and adapting in a fast-paced environment.

Highly Valued Relevant Attributes:

1. Ability to multitask and adapt.
2. Curiosity and eagerness to learn and grow professionally.
3. Self-motivated, detail-oriented, and able to work independently in a fast-paced environment.