Quantitative Jobs in Web3

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Job Position Company Posted Location Salary Tags

Ripple

San Francisco, CA, United States

$72k - $75k

Taurus SA

Geneva, Switzerland

$36k - $62k

Binance

Remote

Crypto.com

Remote

$14k - $23k

BlockFi

New York, NY, United States

$54k - $90k

SALT

Remote

$86k - $110k

SALT

Remote

$86k - $110k

Okcoin

San Francisco, CA, United States

$45k - $75k

Keyrock

Brussels, Belgium

$28k - $72k

Keyrock

Brussels, Belgium

$28k - $72k

Mythical Games

Los Angeles, CA, United States

$36k - $60k

BlockFi

New York, NY, United States

$63k - $90k

Crypto.com

Remote

$14k - $23k

Kronos Research

Taipei, Taiwan

$28k - $33k

Energi Core Limited

New York, NY, United States

$40k - $92k

Quantitative Development Engineer Liquidity Summer 2022 Intern

Ripple
$72k - $75k estimated

This job is closed

Ripple’s mission is to enable payments every way, everywhere for everyone. We believe connecting traditional financial entities like banks, payment providers and corporations with emerging blockchain technologies and users is the path to an open, decentralized, and more inclusive financial future. This Internet of Value gives any internet-enabled person, application or device access to financial services that are transparent, fast, reliable, and cheap. Delivering this vision is a challenge of massive scale spanning $155 trillion in annual cross border fiat payments and the $1.5 trillion market of digital assets that has grown 10X in the last year.

We are looking for interns to join our growing Liquidity Engineering teams charged with delivering a first-of-its-kind liquidity platform-as-a-service to transform Ripple’s global customers. By joining one of our teams, you will contribute in one of the following areas: full-stack software engineering, DevOps, crypto trading platform, machine learning engineering, applied science, or quantitative development. You will partner with teammates and across the Liquidity Engineering organization to build robust solutions that power our liquidity services at scale. You will contribute your own solutions and be mentored by other engineers, contributing to a culture of high standards and technical excellence. As a member of a new initiative, you must be passionate about inventing and delivering customer-focused solutions to ambitious and ambiguous challenges.

WHAT YOU’LL DO:

  • Build, improve, and maintain services that will deliver liquidity to Ripple’s customers, ensuring we deliver the best customer experience of the widest selection of assets at the best price
  • Design and implement scalable and reliable services, analysis, and/or infrastructure
  • Collaborate with partner Liquidity Engineering teams and business stakeholders to build new capabilities to deliver liquidity to Ripple’s customers

Some examples of projects our Liquidity Engineering teams are tackling include:

  • Launching Liquidity Hub, a liquidity platform for enterprises to easily and efficiently source digital assets.
  • Playing a critical role helping to advance Ripple’s development and production infrastructure, including deployment, monitoring, instrumentation, and overall infrastructure management.
  • Determining and delivering optimal liquidity for every customer in the world by contributing to the development of a cost-effective, robust, and scalable crypto trading platform
  • Building end-to-end machine learning-enabled solutions, from forecasting supply and demand to optimizing routing across digital asset venues to pricing and risk management systems.
  • Delivering scalable production machine learning services to solve our liquidity challenges by designing and implementing the infrastructure and tools to create and deploy production models.
  • Building backtest research tools understand the dynamics of FX & Crypto markets based on data

WHAT WE’RE LOOKING FOR:

  • Pursuing a degree in Computer Science or another technical field
  • Coursework / intern experience with software engineering, ideally involving data oriented applications (Python, Java or other programming languages)
  • One or more of the following:
    • Experience building and working with REST/GRPC API endpoints
    • Experience building highly elegant, scalable and responsive web applications
    • Experience with automated testing, continuous delivery and deployment, and load testing.
    • Experience with cloud infrastructure, including platform tools like Kubernetes, container schedulers & runtimes such as Docker, Rkt, or OCI, or Infrastructure-as-Code (e.g. Terraform, CloudFormation, etc.)
    • Experience creating and analyzing large datasets
    • Experience solving problems that involve machine learning or other quantitative techniques, including statistical modeling, time series analysis/forecasting and experimentation, bonus if in finance and trading domains, especially Crypto or FX.

  • Excellent written and verbal communication skills
  • Attention to detail and a commitment to excellence

WHAT WE OFFER:

  • The chance to work in a fast-paced start-up environment with experienced industry leaders
  • A learning environment where you can dive deep into the latest technologies and make an impact
  • Modern office in San Francisco’s Financial District
  • Fully-stocked kitchen with organic snacks, beverages, and coffee drinks
  • Weekly company meeting - ask me anything >
  • Team outings to sports games, happy hours, game nights and more!
#LI-DNI

What is a quantitative career?

A quantitative career is a profession that involves using mathematical, statistical, and computational techniques to solve problems and make decisions in a wide range of industries, including finance, engineering, healthcare, and technology

A quantitative career in Web3 involves using mathematical, statistical, and computational techniques to analyze and optimize decentralized finance (DeFi) protocols, blockchain networks, and other Web3 applications

Some examples of quantitative careers include:

  1. Quantitative Analyst: A professional who uses mathematical models and statistical analysis to identify and quantify risks and opportunities in financial markets.
  2. Data Scientist: A professional who analyzes complex data using statistical methods, machine learning, and other techniques to help organizations make data-driven decisions.
  3. Actuary: A professional who uses mathematical models and statistical analysis to assess risk and uncertainty in the insurance and finance industries.
  4. Quantitative Developer: A professional who develops and implements quantitative models and trading strategies for financial institutions and other organizations.
  5. Operations Research Analyst: A professional who uses mathematical and statistical techniques to optimize complex systems, such as supply chains, transportation networks, and manufacturing processes.