Advanced Alternative Asset Trading

Powered by Machine Learning & Artificial Intelligence

Millisecond to Daily Strategies
AI-Driven Analytics
Alternative Data Insights

World-Class Expertise

Elite Background

Our team members have distinguished careers at leading global institutions and top-tier investment firms.

Academic Excellence

Several team members are professors at prestigious universities, bringing cutting-edge research to our strategies.

Deep Experience

Decades of combined expertise in quantitative trading, risk management, and financial technology.

Our Strategy

Sophisticated multi-horizon trading powered by advanced AI and alternative data

Alternative Assets Focus

We specialize in alternative asset classes, leveraging unique market inefficiencies and opportunities across diverse investment landscapes.

AI & Machine Learning

Advanced neural networks and machine learning algorithms process vast amounts of data to identify patterns and generate alpha.

  • Deep learning models
  • Reinforcement learning
  • Natural language processing
  • Ensemble methods

Multi-Horizon Strategies

Our strategies span multiple time horizons to capture opportunities across the spectrum:

  • High-frequency: Millisecond-level execution
  • Intraday: Minute to hour timeframes
  • Short-term: Daily to weekly positions
  • Medium-term: Multi-week strategies

Alternative Data

We harness non-traditional data sources to gain unique market insights:

  • Satellite imagery
  • Social media sentiment
  • Web traffic patterns
  • Supply chain data
  • Credit card transactions

Risk Management

Sophisticated risk controls and portfolio optimization ensure capital preservation while maximizing returns.

Careers

Join a team of exceptional professionals at the forefront of quantitative finance

At WMLake Capital, we're building the future of alternative asset trading. We seek talented individuals who are passionate about technology, finance, and innovation.

Quantitative Researchers

Develop cutting-edge trading strategies using machine learning and statistical methods.

Requirements:

  • PhD or Master's in Computer Science, Mathematics, Physics, or related fields
  • Strong programming skills (Python, C++)
  • Experience with ML frameworks
  • Deep understanding of statistics and probability

Machine Learning Engineers

Build and optimize AI systems that power our trading infrastructure.

Requirements:

  • Strong background in machine learning and deep learning
  • Experience with TensorFlow, PyTorch, or similar
  • Proficiency in distributed computing
  • Production ML systems experience

Quantitative Developers

Create high-performance trading systems and data processing pipelines.

Requirements:

  • Expert-level C++ or Python programming
  • Low-latency system design experience
  • Knowledge of financial markets
  • Strong algorithms and data structures background

Data Scientists

Extract insights from alternative data sources to drive investment decisions.

Requirements:

  • Advanced degree in quantitative field
  • Expertise in data analysis and visualization
  • Experience with big data technologies
  • Strong statistical modeling skills

Why WMLake Capital?

Work on challenging problems at the intersection of AI and finance

Collaborate with world-class researchers and practitioners

Access to cutting-edge technology and data resources

Continuous learning and professional development

Contact Us

Get in touch with our team

Email

[email protected]

For general inquiries

Careers

[email protected]

For career opportunities

Investor Relations

[email protected]

For investment inquiries