Internship

Quant Research Internship

Confirmed live in the last 24 hours

Blockhouse

Blockhouse

11-50 employees

Develops decentralized security and privacy technologies

Fintech
Cybersecurity
Crypto & Web3

New York, NY, USA

Category
Quantitative Research
Quantitative Finance
Required Skills
Python
Data Science
Data Analysis
Requirements
  • Currently pursuing or having completed a Master's or PhD in a quantitative field such as Mathematical Finance, Financial Engineering, Mathematics, or Statistics.
  • 6 months to 1 year of hands-on experience analyzing trade data in any asset class is strongly encouraged.
  • Must have a deep understanding of stochastic differential equations and how to solve stochastic control problems, along with a strong grasp of advanced mathematics and statistics.
  • Experienced in reading, understanding, and applying findings from academic research papers to practical use cases in quantitative finance.
  • Proficient in Python and familiar with relevant libraries and tools used in quantitative finance.
  • Detail-oriented with a rigorous approach to analysis and a natural curiosity for exploring new methodologies.
  • Possesses outstanding communication skills, capable of conveying complex quantitative concepts and results effectively across multidisciplinary teams.
Responsibilities
  • Contribute to the development and implementation of advanced mathematical models for Transaction Cost Analysis (TCA), price impact modeling, and other quantitative problems across multiple asset classes.
  • Proactively learn and translate complex academic papers and quantitative studies into practical, deployable models for slippage calculations and trading optimization.
  • Contribute to the writing and publication of research papers on innovative techniques for measuring slippage, price impact, and optimizing trades across diverse markets.
  • Work closely with our team of quant researchers and data scientists to push the boundaries of quantitative finance in a multidisciplinary context.
  • Stay abreast of the latest developments in quantitative finance and contribute to the continuous improvement of our models and methodologies, with a focus on trading analytics and market dynamics.

Blockhouse develops decentralized technologies that prioritize security and privacy in digital systems. The company focuses on blockchain and trusted execution environments (TEEs), creating a distributed platform made up of secure microservices that operate within these TEEs. This setup allows Blockhouse to provide high-level security while maintaining performance. The company earns revenue through partnerships, licensing its technology, and offering key management services for various digital infrastructures. Blockhouse aims to foster a secure digital society by promoting trusted and trustless computing, which empowers individuals to have control over their personal data in a decentralized environment.

Company Stage

N/A

Total Funding

N/A

Headquarters

Oxford, United Kingdom

Founded

2018

Growth & Insights
Headcount

6 month growth

36%

1 year growth

36%

2 year growth

36%
Simplify Jobs

Simplify's Take

What believers are saying

  • Increased adoption of confidential computing enhances data security for enterprises.
  • Zero-trust architecture rise drives demand for TBTL's security-focused technologies.
  • EU's digital sovereignty focus encourages adoption of decentralized technologies.

What critics are saying

  • Emerging blockchain startups offer similar solutions at lower costs.
  • Potential vulnerabilities in TEEs could be exploited by cyber-attacks.
  • Regulatory scrutiny on blockchain technologies may impact operational flexibility.

What makes Blockhouse unique

  • TBTL focuses on decentralized technologies ensuring security and privacy in digital systems.
  • The company offers a distributed platform with hardened microservices in TEEs.
  • TBTL's business model includes partnerships, licensing, and key management services.

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