Systematic Fast Trading Intern

About Man Group

Man Group is a global alternative investment management firm focused on pursuing outperformance for sophisticated clients via its Systematic, Discretionary, and Solutions offerings. Powered by talent and advanced technology, its investment strategies span public and private markets across all major asset classes, with a significant focus on alternatives.

The Team

Man Systematics’ Fast Trading Strategies (FTS) team is responsible for the development of high Sharpe, high-frequency trading strategies across all asset classes. The team manages a large and successful portfolio across both global futures and cash markets. The FTS team is responsible for the full end-to-end development of the fast alpha portfolio, using techniques such as ML, event driven, and microstructure-based methods. They build customized monetization stacks and optimize trading and order placement with dedicated high-frequency infrastructure. This internship is based in the New York office, which focuses on high-frequency alpha research, trading, and infrastructure.

Who Should Apply?

• PhD students interested in an MLE/QR internship.
• Candidates with strong academic achievement in highly technical degree programs.
• Candidates interested in a summer internship (expected to be between 10 – 12 weeks).
• Penultimate year students only.

Purpose of the Role

• MLE Role: Ideal for individuals passionate about software focused on machine learning applications such as MLOps and research workflows. Requires experience coding in a variety of languages, especially Python, and knowledge of ML algorithms and research processes.
• QR Role: Ideal for individuals passionate about using high frequency tick data and machine learning algorithms to predict asset returns and converting models into profitable trading strategies. Requires strong programming skills in a variety of languages, especially Python.

Key Responsibilities

• Developing high Sharpe, high-frequency trading strategies.
• Capturing fast alphas using various techniques (ML, event driven, microstructure-based).
• Building customized monetization stacks.
• Optimizing trading and order placement with high-frequency infrastructure.
• Deploying models and working closely with MLOps.
• Using high frequency tick data and machine learning algorithms to predict asset returns.
• Converting models into profitable trading strategies.

Requirements & Tech Stack

• Experience coding in a variety of languages, especially Python.
• Knowledge of ML algorithms and research processes.
• Experience with high frequency tick data.
• Familiarity with MLOps (for MLE role).

Qualifications

• Strong academic achievement in highly technical degree programs (PhD students preferred).
• Previous ML or statistical research internship experience in finance, technology, or academia is strongly preferred.

Working Here

• Performance-driven, meritocratic culture with a flat, open, transparent, and collaborative structure.
• Ample opportunity to grow and have a significant impact.
• Engaged with the broader research and academic community, as well as industry contributors.
• Modern office in central Midtown, conveniently located near Central Park.
• Opportunities for professional development.
• Flexible working arrangements available.

Compensation

• US Pay Range: $50 USD - $60 USD (base salary)
• Compensation packages would also include benefits and a discretionary bonus.

Benefits

• Competitive holiday entitlements.
• Pension/401k.
• Life and long-term disability coverage.
• Group sick pay.
• Enhanced parental leave and long-service leave.
• Two annual 'Mankind' days of paid leave for community volunteering.
• Depending on location, may include private medical coverage, discounted gym membership options, and pet insurance.