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Wizard Quant Co-founder Xin Feng: AI has Arrived, Embracing the Next Era of Quantitative Investment

关于执行事务合伙人、普通合伙人及实际控制人变更之临时公告

关于上海宽德私募基金管理中心（有限合伙）名称变更公告

Exclusive: Wizard Quant Co-founder Xin Feng on Striving for Excellence in Quantitative Management

Wizard Quant 2024 Summer Internship Recruitment Open for Application!

WizardQuant' s all-star team is made up with both Wall Street veterans and smart talented rookies. The spirit of discovery and a relentless pursuit of excellence keep driving us forward.

01. Pioneer

02. Fighter

03. Responsibility

Integrity, perceptiveness, enthusiasm, innovation, pioneering ...... These are the tags belonging to our people. Listen to their stories to learn what it's like to work at here.

Wizard Quant is a full-service quantitative hedge fund in China. Based on advanced research、trading and asset management system, we have sustainable profitability in domestic futures, stocks, options and other mainstream markets.

Founded in 2014, we have been working with the dream of building the world's top Chinese quantitative hedge fund, and continuously working diligently and eagerly looking forward to each and everyone of our fellow travellers.

Wizard Blog

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From low-latency infrastructure to AI cluster customization, from hardware design to compilation and optimization, from efficient AI training to extremely fast inference, our IT team keeps expanding the boundaries and develops a cross-platform, cross-scene, software and hardware integrated computing ecology.

Talent is the most valueable asset in WizardQuant. We spend time extensively to hire and cultivate extraordinary people. We are top scorers, PhDs of top institutions, International Math Olympiad medalists. We have traversed the world, working for the likes of Two Sigma, Citadel, Point 72 and more. Brightest minds from all parts of the world come here to collaborate on challenging problems, learn from each other and advance the computing technologies in financial market.

Research Team is the core of the whole company. They work collaboratively to create, review, and improve profitable strategy models with advanced and rigorous statistical and machine learning tools. They keep building new competitive advantages on top of their current portfolios.

Human resources, administration, risk control &compliance, brand, product operation, channel development, finance .... Whether working directly with clients and candidates or managing important internal initiatives, you will be part of an exceptional team making a measurable difference across the business.

50% of the partners have joined the company since their internship, 80% of R&D leaders come from freshmen training. Mentor offers each team member a customized training program and a well-defined professional path, to ensure rapid growth of everyone.

Infinite Development

Our extraordinary team members include Wall Street veterans from Citadel, Two Sigma, Point72, BNP Paribas and other world-renowned financial institutions, as well as PhDs from Tsinghua, Peking University, MIT, Cornell, UCB, Columbia, NYU and other prestigious schools. There are also top scorers and Olympiads medalists. We come together, set ambitous goals and make unexpected breakthroughs.

Extraordinary Teammates

Salaries, bonuses and funds，each employee can grow with the company and share the benefits as well.

Incentive Program

WizardQuant 2024 Campus Recruitment Now Open!

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Explore the core functionalities of the WQ platform

Core Technologies

Create an autonomous toolchain and thoroughly deploy hardware-software codesign techniques, to approach the physical limits of hardware.

High-Frequency Trading

One complete and efficient feature engineering platform; modern and sophisticated portfolio frameworks, in-depth and detailed market impact models.

Statistical Arbitrage

Embrace the new generation of parallel paradigm, integrate HPC into AI scenarios, and build highly optimized machine learning tools throughout the entire process of data processing, training, optimization, inference and deployment, to explore new computing frontiers.

Machine Learning

Meet the Wizards

WizardQuant - The Magic of Computing

01 Source

Global Data
Collection System

02 Storage

High Performance Storage System

03 Research

High Concurrency Strategy
Development Platform

04 Optimization

Portfolio Construction Engine

Technologies

<h1>Job Description</h1>
<ul>
<li>Conduct research and analyze enormous data sets to generate alphas, and evaluate their marginal effectiveness</li>
<li>Develop profitable predictive trading models, and contribute to portfolio optimization</li>
<li>Utilize new data sets to develop new strategies</li>
<li>Collaborate closely with quant developers to drive productivity</li>
</ul>
<h1>Qualification</h1>
<ul>
<li>Bachelor/Master/Ph. D students from top universities, majoring in machine learning, EECS, statistics, mathematics, physics, operation research, economics, finance or other relevant fields</li>
<li>Solid knowledge in mathematics and statistics</li>
<li>Strong programming skills in Python/R/MATLAB, with experience in data analysis and developing models</li>
<li>Collaborative mindset with strong independent research ability</li>
<li>Detail-oriented, full of curiosity and creativity, and passionate about solving problems</li>
</ul>


Quantitative Researcher

<h1>Job Description</h1>
<ul>
<li>Combine machine learning techniques and financial insights to analyze enormous datasets, create investment strategies and develop sophisticated models</li>
<li>Develop and evaluate new machine learning algorithms and optimization methods</li>
<li>Keep up with state-of-the-art technologies and methods in this industry and be willing to share with team on a regular basis</li>
</ul>
<h1>Qualifications</h1>
<ul>
<li>Bachelor/Master/Ph. D students from top universities, majoring in machine learning, EECS, statistics, mathematics, physics, operation research or other relevant fields</li>
<li>Strong programming skills in Python/R/MATLAB, with experience in data analysis and developing models</li>
<li>Familiar with at least one mainstream deep learning framework such as TensorFlow and PyTorch</li>
<li>Fully understand the applicability and limitation of mainstream machine learning algorithms (e.g. CNN, RNN, LSTM, etc.) and can flexibly integrate his/her knowledge into industry scenarios</li>
<li>Collaborative mindset with strong independent research ability</li>
</ul>
<h1>Other Skills or Experience We Highly Value</h1>
<ul>
<li>Strong programming skills in C/C++, or previously won ACM/IOI/NOI awards</li>
<li>Understand distributed computing and storage frameworks, such as Spark, Hadoop, etc.</li>
<li>Worked on technical blogs such as Github, or participated in well-known open source projects.</li>
<li>Obtained excellent results in machine learning competitions, such as Kaggle/KDD/ImageNet, etc.</li>
<li>As a major contributor, published papers for top conference, such as NeurIPS/ICML/IJCAI/PAMI/CVPR/ACL/SIGKDD, etc.</li>
</ul>


Machine Learning Researcher

<h1>Job Description</h1>
<ul>
<li>Design, develop and maintain research pipelines and tools for data processing, strategy simulation and alpha generation</li>
<li>Build the trading platform to deploy quant researchers’ trading strategies</li>
<li>Contribute to the design and optimization of machine learning platforms, improve the computing efficiency</li>
<li>Continuously optimize research and trading systems</li>
</ul>
<h1>Qualifications</h1>
<ul>
<li>Bachelor/Master/Ph. D students from top universities, majoring in computer science, software engineer, EE or other relevant fields</li>
<li>Solid knowledge in mathematics, statistics, and computer science</li>
<li>In-depth understanding of computer architecture and operation systems</li>
<li>Proficiency in C, Modern C++ and Python, and rich experience in data analysis</li>
<li>A self-starter, motivated to face technical challenges and uncover hidden problems</li>
</ul>
<h1>Other Skills or Experience We Highly Value</h1>
<ul>
<li>Familiar with heterogeneous computing and deep learning infrastructure</li>
<li>Conducted supercomputing related research</li>
<li>Experience in building compilers</li>
</ul>
