Job Description

We are working on behalf of a top performing trading firm, who are looking for a Senior Quantitative Researcher to partner with the Senior Portfolio Manager to create alpha from various data sources for the systematic trading of global multi-asset class strategies.

Location

Berkeley, CA (open to US-based candidates)

Principal Responsibilities

• Work alongside the Senior Portfolio Manager on building prediction and portfolio optimisation pipelines:
• Understand the potential prediction power from the data source and identify alphas
• Develop state-of-the-art ML algorithms for prediction and optimisation
• Performing various statistical analysis to ensure the robustness
• Mentor and guide junior team members
• Combine sound financial insights and statistical learning techniques to explore, analyze, and harness a large variety of datasets
• Aid in developing and extending the team’s proprietary research platform
• Collaborate with the PM and the trading group in a transparent environment, engaging with the whole investment process
• Stay current on state-of-the-art technologies and tools including technical libraries, computing environments and academic research

Preferred Technical Skills

• Strongly skilled in Python and R (Pandas, NumPy, TensorFlow, PyTorch, etc.)
• Ph.D. degree in Computer Science, Mathematics, Statistics, or related STEM field from top ranked University
• Demonstrated knowledge of quantitative finance, mathematical modelling, statistical analysis, regression, and probability theory
• Excellent communication, problem-solving, and analytical skills, with the ability to quickly understand and apply complex concepts
• Experience and success working with large and diverse data sets

Preferred Experience

• 4+ years of experience working in a systematic trading environment
• 4+ years of hands-on experience working with multiple vendor data sets and, in particular, manipulating data (assessing, cleaning, creating features, etc.)
• Established alpha research pipeline with production grade output
• Strong experience in evaluating alphas with statistical methods
• Experience collaborating effectively with cross-functional teams, multitasking and adapting in a fast-paced environment

Highly Valued Relevant Experience

• Experience working with big data sets
• Experience working in an autonomous, fast-paced environment

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