| Job Position | Company | Posted | Location | Salary | Tags |
|---|---|---|---|---|---|
Crypto.com | Remote | $14k - $23k | |||
Binance | Remote |
| |||
Mirana | Singapore, Singapore | $40k - $56k | |||
Crypto.com | Remote | $14k - $23k | |||
| Learn job-ready web3 skills on your schedule with 1-on-1 support & get a job, or your money back. | | by Metana Bootcamp Info | |||
Kronos Research | Taipei, Taiwan | $28k - $33k | |||
Altonomy | Singapore, Singapore |
|
This job is closed
About Crypto.com
Crypto.com was founded in 2016 on a simple belief: it's a basic human right for everyone to control their money, data and identity. With over 10 million users on its platform today, Crypto.com provides a powerful alternative to traditional financial services, turning its vision of "cryptocurrency in every wallet" into reality, one customer at a time. Crypto.com is built on a solid foundation of security, privacy and compliance and is the first cryptocurrency company in the world to have CCSS Level 3, ISO27001:2013 and PCI: DSS 3.2.1, Level 1 compliance. Crypto.com is headquartered in Hong Kong with a 1000+ strong team.
For more information, please visit www.crypto.com.
Responsibilities
- research/implement / debug strategies based on tick-level / alternative data High/Mid/Low frequencies delta1 and volatility
- Monitor live strategy performance/debug issues (i.e. specific to crypto exchanges data)
- Contribute and maintain python crypto derivatives delta1 and options analytics/trading pricing/backtesting/optimisation library and webapp tools (flask,javascript)
- Applies machine learning techniques such as feature selection /transformations/normalisation to explore alpha strategies
- Perform data cleaning and identifying outliers
- Implement/back-test cutting-edge ideas and models derived from research papers
- Previous experience in trading firm/hedge fund/investment bank/exchange (2y+)
- Solid cryptocurrency trading experience
- Masters/PhD in Physics/Maths/Applied Maths/Statistics from top schools
- Excellent python
- Very good math/probability background
- Technical must-haves:
- Predictive machine learning implementations ( tensorflow / xgboost/ sklearn)
- Backtesting framework (e.g. backtrader)
- Scientific , high performance python (3y+)
- Experience in working with Pandas dataframes of several Gb (2y+)
- Unix scripting, Automation scripts
- Git
- Technical good-to-haves : Flask , Javascript ,HTML, crypto exchanges connectivity /data download , SQL, Xgboost, Tensorflow, Scikit learn, Seaborn
- We offer an attractive compensation package working in a cutting-edge field of Fintech.
- Huge responsibilities from Day 1. Be the owner of your own learning curve. The possibilities are limitless and depend on you
- You get to work in a very dynamic environment and be part of an international team
- You will get to have involvement in developing brand new products from scratch using latest technologies alongside with a passionate and talented team
What does a Quantitative Researcher do?
A Quantitative Researcher is a professional who conducts research in the field of finance, economics, or related fields using quantitative methods such as statistical analysis and mathematical modeling
They typically work in the financial industry, including investment banks, hedge funds, and asset management firms
The job of a Quantitative Researcher can vary depending on the employer and industry, but generally, they use quantitative techniques to analyze financial data and develop models that can be used to make investment decisions
A Quantitative Researcher in Web3 is a professional who conducts research using quantitative methods in the context of decentralized finance (DeFi) and other Web3 applications
They work to understand the behavior of decentralized systems and develop models that can be used to optimize investment strategies
Some specific tasks that a Quantitative Researcher may be responsible for include:
- Developing models for decentralized finance: Quantitative Researchers in Web3 may develop mathematical models and algorithms that can be used to analyze decentralized financial systems, such as decentralized exchanges (DEXs), lending protocols, and prediction markets. These models may be used to assess risk, predict market behavior, and optimize investment strategies.
- Conducting on-chain data analysis: Quantitative Researchers in Web3 analyze on-chain data from decentralized platforms to understand user behavior and network activity. They may use statistical techniques such as regression analysis and machine learning to analyze this data and identify patterns that can be used to inform investment strategies.
- Writing research reports: Quantitative Researchers in Web3 write reports summarizing their research findings and recommendations for investment strategies. These reports may be used by traders, portfolio managers, and other decision-makers within the organization.
- Collaborating with other teams: Quantitative Researchers in Web3 may work closely with other teams within the organization, such as developers, quants, and traders, to develop and implement investment strategies that leverage their research insights.