Data Science Jobs in Web3

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Job Position Company Posted Location Salary Tags

RWA.xyz

New York, NY, United States

$90k - $100k

Chainalysis

Toronto, Canada

$76k - $87k

Crypto.com

Hong Kong, Hong Kong

$27k - $67k

Bitso

Latin America

$122k - $201k

Bitwise Asset Management

San Francisco, CA, United States

$110k - $125k

Keyrock

Brussels, Belgium

$112k - $156k

Launchpadtechnologiesinc

Latam

$79k - $92k

Binance

Remote

Gate.io

APAC

$80k - $100k

Horizon Blockchain Games

Toronto, Canada

$84k - $90k

Shakepay

Toronto, Canada

$84k - $93k

Whatnot

New York, NY, United States

$240k - $320k

Chainalysis

New York, NY, United States

$90k - $100k

Integra

Austin, TX, United States

$88k - $103k

RWA.xyz
$90k - $100k estimated
New York Brooklyn USA

About RWA.xyz

RWA.xyz is the leading data and analytics platform for tokenized real-world assets. Our customers are institutions and startups at the forefront of financial innovation like Moody's, Chainlink, and Aptos. Our data has been cited extensively by the US Treasury Department, McKinsey, JP Morgan, and many others.

We're backed by top-tier investors: Jump, Archetype, and Nascent. Our team's backgrounds span across tech, finance, and crypto, including alumni from Amazon, Microsoft, Coinbase, and Morgan Stanley.

We're looking to bring on a new team member to help us scale our data systems across new blockchain networks and protocols.

Overview

Role: Blockchain Data Engineer

Type: Individual Contributor

Level: Early-Mid Career

Location: IRL in NYC preferred

Qualifications

None of these are strict requirements—we believe great candidates can come from many different backgrounds.

  • Experience building data systems with PySpark, preferably on DataBricks.

  • Experience designing relational database schemas

  • Experience with cloud infrastructure DevOps

  • Excellent communication ability

  • Strong sense of ownership and craftsmanship

  • Can move quickly and accurately under conditions of uncertainty without supervision

Bonus points if you have previous blockchain data, early-stage startup, or finance experience!

Responsibilities

As a data engineer, your responsibilities will include:

  • Building our core data systems and API

  • Collaborating with product engineers to ship new features

  • Increasing team productivity by improving the development lifecycle

Since we’re a startup, in addition to the above, you’ll have the chance to be involved in other areas of the business like product, growth, recruiting, and fundraising.

Our Process

  • The first step is a phone screen with a recruiter for us to learn some of the basics about your background.

  • The second step is meeting Charlie, our CTO. He’ll ask in-depth questions about your work history, as well as give you an overview of our company and culture.

  • The third step is a technical take-home assignment where you’ll solve a problem similar to the ones we face every day.

  • After the take-home, you’ll meet us on-site to whiteboard a system design problem and enjoy a delicious lunch with the team!

  • Finally, we like to do a paid trial run, where you’ll be working with us over a weekend or part-time during the week. This lets both sides make a more informed decision about working together.

  • Afterwards, we’ll ask for references with past colleagues and compile a formal offer

What does a data scientist in web3 do?

A data scientist in web3 is a type of data scientist who focuses on working with data related to the development of web-based technologies and applications that are part of the larger web3 ecosystem

This can include working with data from decentralized applications (DApps), blockchain networks, and other types of distributed and decentralized systems

In general, a data scientist in web3 is responsible for using data analysis and machine learning techniques to help organizations and individuals understand, interpret, and make decisions based on the data generated by these systems

Some specific tasks that a data scientist in web3 might be involved in include developing predictive models, conducting research, and creating data visualizations.