Quantitative Analyst Jobs in Web3
65 jobs found
Job Position | Company | Posted | Location | Salary | Tags |
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Gsrmarkets | Remote | $150k - $200k | |||
Binance | Asia |
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DTG Finance & Capital Markets | New York, NY, United States | $76k - $80k | |||
Cruz Money Pty Ltd | Remote |
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Learn job-ready web3 skills on your schedule with 1-on-1 support & get a job, or your money back. | | by Metana Bootcamp Info | |||
Binance | Asia |
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Confusion Capital | Remote | $180k - $220k | |||
Confusion Capital | Remote | $180k - $220k | |||
Confusion Capital | Remote | $180k - $220k | |||
Token Metrics | Barcelona, Spain | $89k - $102k | |||
Impossible Cloud | Hamburg, Germany | $90k - $90k | |||
GSR Markets | Remote | $180k - $220k | |||
Kronos Research | Shanghai, China | $63k - $77k | |||
Kronos Research | Taipei, Taiwan | $32k - $81k | |||
Asymmetric Capital | Remote | $72k - $110k | |||
Token Metrics | Panama City, Panama | $89k - $102k |
Job Title: Quantitative Analyst Worksite: Jersey City, NJ 07302 Wage: $150,000 - $200,000 per year Job Description:Â Formulate and apply modeling and other optimizing methods to develop and interpret information to improve the market and counterparty risk for the automated market making and trading business.Â
Responsible for implementing and testing new models. Collaborate with analytics team to develop and improve models for pricing, VaR, and stress testing. Support pricing and risk management analytics, working closely with Risk, Trading, and Technology. Deliver consistently on the full cycle of model development, implementation, validation, analysis, and model confirmation. Support the development and implementation quantitative models with emphasis on risk management, reporting controls and transparency. Enhance governance and controls by maintaining data pipeline to source and save live/historical data from different sources (exchanges and data platforms. Build risk models, hedging tools and perp trading strategies on top of an in-house grouping methodology. Collaborate with quant traders, developers and risk team. Contribute to analyses required by internal and external stakeholders.
Qualifications: Master’s degree in a quantitative discipline such as Financial Engineering, Applied Mathematics, Statistics, Physics, Computer Science, foreign equivalent or closely related field. One (1) year of experience in job offered, Model Validation Analyst or closely related trading/risk environment. Required skills: Position requires one (1) year of experience in: Â
End-to-end validations; Regulatory market risk and xVA counterparty risk models; Model validation methodology; Risk reporting report in power BI; Market risk and liquidity risk models; Quantitative and qualitive analytical tools; Python (Pandas, NumPy), C++, and MySqL programming; and CVA VAR.
Multiple openings.  Key Benefits  GSR offers the following core benefits for its US employees. The majority require an individual to be employed for at least 30 hours a week. Â
Participation in a bi-annual discretionary cash bonus scheme. Medical, dental and vision insurance for your immediate dependents. Premiums are fully paid for by the company. A company funded Health Reimbursement Account, to be used against qualifying medical expenses. Ability to contribute to a Healthcare Flexible Spending Account and/or Dependent Care Flexible Spending Account. Fertility and family planning support, including a financial contribution from the company. Life and accident insurance. Premiums are fully paid for by the company. Ability to purchase additional voluntary life insurance for you and your immediate dependents. Short and long term disability insurance. Premiums are fully paid for by the company. 401k employer matching contributions. Ability to contribute towards a Commuter Benefit Plan. Employee Assistance Programme. Generous paid time off (30 days per year for full time employees).
 Apply Now.Â
What do quantitative analyst do?
A quantitative analyst, also known as a 'quant', is a professional who uses quantitative techniques to develop and implement financial models, analyze data, and make investment decisions
Quants are typically employed by financial institutions such as hedge funds, investment banks, and asset management firms
In Web3 quantitative analysts can leverage their expertise in data analysis and modeling to inform investment decisions and help build new decentralized systems and applications
The job of a quantitative analyst can vary depending on the employer and industry, but generally, they use mathematical and statistical models to analyze financial data and make informed investment decisions
They may use programming languages like Python, R, or MATLAB to develop these models
Some specific tasks that a quantitative analyst may be responsible for include:
- Analyzing financial data and identifying patterns and trends.
- Developing and testing mathematical models to predict financial market behavior.
- Designing and implementing trading strategies based on quantitative analysis.
- Decentralized finance (DeFi) analysis: Quants can analyze various decentralized financial protocols to identify opportunities for investment and assess risks associated with these protocols. They may develop models to predict the behavior of decentralized financial instruments and evaluate their performance.
- Cryptocurrency market analysis: Quants can analyze cryptocurrency markets and identify patterns and trends that may be used to inform trading strategies. They can also develop models to predict the price movements of cryptocurrencies based on various factors such as supply and demand, market sentiment, and adoption rates.
- Smart contract analysis: Smart contracts are self-executing contracts with the terms of the agreement directly written into code. Quants can analyze smart contract code to identify potential vulnerabilities and assess the risk associated with the execution of the contract.
- Web3 data analysis: Quants can analyze data from various Web3 platforms and protocols to identify trends and make informed decisions. This may involve developing new techniques for analyzing decentralized data, such as utilizing data from on-chain transactions to gain insights into user behavior and network activity.