Data Infrastructure Researcher
Wunder Fund
Job Overview
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Job Description
About Wunder Fund
Wunder Fund, established in 2014, specializes in High-Frequency Algorithmic Trading (HFT). We trade on numerous exchanges worldwide, encompassing both traditional and cryptocurrency markets. Our current daily trading turnover is approximately ~$8 billion.
We are expanding our Market Data team and are looking for a Data Infrastructure Researcher.
The Importance of This Role
Our quants utilize backtesting – an exchange simulator – to test ideas and develop trading strategies.
Accurate backtesting requires extremely careful handling of historical data. Initially, we store raw online trading data in the simplest and most reliable way possible. Data from different exchanges arrives in various formats and can be highly diverse. Therefore, after storage, we daily transform this data into our internal unified format. Subsequently, the quality of the processed data is verified against numerous parameters using a specialized checker program.
It is crucial that the prepared data can be relied upon for simulation – it must be free of gaps and artifacts, and maximally correspond to what actually happened on the exchange. Garbage in – garbage out.
What You'll Be Doing and Why It's Interesting
In this position, you will develop both as an engineer and as a researcher.
You will:
- Investigate data losses and discrepancies – these still sometimes occur, often due to new and non-trivial reasons. Each individual case of inconsistency requires a thoughtful approach and thorough investigation.
- Develop exchange data parsers.
- Build and maintain pipelines: manage the infrastructure for collecting and processing exchange data, which is written in Python 3 and C++20. The processing infrastructure consists of several stages and runs distributedly in Google Cloud. There are many non-trivial tasks.
How to Identify with This Role
- Interest in development and how complex systems are designed.
- Love for data. You will spend a lot of time meticulously examining exchange data.
- Desire to get to the bottom of things. You don't abandon a task if several of your ideas fail; instead, you move from failure to failure with increasing enthusiasm.
- Inquisitive mind and interest in research.
If you recognize yourself in this description, you will likely find it interesting. We have assembled a team of super-strong specialists – graduates of Moscow State University and MIPT, Kagglers, SHAD students, winners of international olympiads, and top programmers and mathematicians.
Requirements
- Commercial development experience in Python and C++.
- Be an experienced practitioner in the method of close data scrutiny.
- A plus: successes in Kaggle competitions, SHAD, successes in ICPC and other olympiads.
Conditions
- Minimum bureaucracy, a small team of strong specialists, with whom to discuss ideas.
- Full remote work.
- After the probation period, we assist with relocation / obtaining a residence permit, etc., if desired. If you are of conscription age and in Russia, we can assist with deferment.
- Twice a year for a couple of months, we rent a large villa where you can work and live together (we've been to Thailand, Turkey, Bali).
- Salary range – $5-7k net.
A short video about our infrastructure and general company insights: https://youtu.be/662q9FVqp50
Key skills/competency
- Python Development
- C++ Programming
- Data Pipeline Engineering
- Market Data Processing
- Data Quality Assurance
- Distributed Systems (GCP)
- Algorithmic Trading (HFT)
- Problem Solving (Data Discrepancies)
- Linux Environment
- Research & Investigation
How to Get Hired at Wunder Fund
- Research Wunder Fund's HFT culture: Study their mission, values, recent news, and employee testimonials on LinkedIn and Glassdoor.
- Customize your resume for data quality: Highlight experience in data integrity, parsing, pipeline development, and investigative problem-solving.
- Showcase Python/C++ expertise: Provide examples of robust, high-performance data infrastructure projects or relevant Kaggle success.
- Prepare for deep technical interviews: Focus on distributed systems, data processing, and debugging complex data issues.
- Demonstrate analytical curiosity: Be ready to discuss how you tackle non-trivial data anomalies and complex system challenges.
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