Python Software Engineer at Jump Trading | AU | Rezi

Python Software Engineer at Jump Trading

Python Software Engineer

Jump Trading · AU

2 weeks ago

Python Software Engineer

Jump Trading · AU

15 days ago
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About the Role

Jump Trading Group is committed to world-class research, empowering exceptional talents in Mathematics, Physics, and Computer Science to apply cutting-edge research to global financial markets. Our culture fosters innovation, creativity, and collaboration. The Data team is building a world-class Data Platform with a centralized source of vendor and proprietary research data. This is a high-visibility initiative where the engineer will help shape the platform as it expands into proprietary datasets. The Derived Data team builds analytical datasets that trading and research rely on, and we are looking for a skilled Software Engineer to normalize and make this data available at massive scale.

Responsibilities

  • Work with a variety of datasets, providing a scalable, centralized, validated representation for consumers.
  • Review and understand various datasets, liaising with external vendors as needed.
  • Design, build, and maintain systems that calculate bars and residuals from market data, including streaming data.
  • Extend the derived-data platform to additional analytics such as curves, volatility surfaces, and greeks.
  • Work closely with trading and research teams to understand their needs and deliver calculations.
  • Contribute to APAC production support, ensuring continuity across time-zone handovers.
  • Document technical solutions and calculations clearly, translating complex methodology for non-technical stakeholders.

Requirements

  • 5+ years of software engineering experience.
  • 5+ years working on large sets of data and direct experience calculating bars and residuals from market data.
  • Good understanding of trading and research, and how trading teams work with analytical research.
  • Strong unit-testing / test-driven coding style.
  • Experience working with various data storage formats, filesystems, and event queues preferred.
  • Hands-on experience working within a Linux environment.
  • Reliable and predictable availability.

Skills

  • Python
  • Rust
  • C++
  • Mandarin
  • Communication
  • Analytical skills
  • Problem-solving skills

Experience Level

  • 5+ years

About the Company

  • Jump Trading Group is committed to world class research.
  • We empower exceptional talents in Mathematics, Physics, and Computer Science to seek scientific boundaries, push through them, and apply cutting edge research to global financial markets.
  • Our culture is unique. Constant innovation requires fearlessness, creativity, intellectual honesty, and a relentless competitive streak.
  • We believe in winning together and unlocking unique individual talent by incenting collaboration and mutual respect.
  • At Jump, research outcomes drive more than superior risk adjusted returns.
  • We design, develop, and deploy technologies that change our world, fund start-ups across industries, and partner with leading global research organizations and universities to solve problems.
  • Our Data team is responsible for building a world class Data Platform with a centralized source of vendor and proprietary research data.
  • This is a growing, high-visibility initiative, not greenfield, but early enough that this engineer will help shape it, with access across the entire platform as the team expands into proprietary datasets.
  • The Vendor Data Group operates in a very dynamic environment utilizing a sophisticated and diverse technology stack, interfacing with all aspects of the firm (from Trading, Research, and Technology to Risk, Middle Office and Accounting) giving individuals within the group a full 360-degree view of Jump.
  • The Derived Data team, part of the Vendor Data Group, builds the analytical datasets that trading and research rely on: bars and residuals computed from market data, extending to curves, volatility surfaces, greeks, and other derived signals.
  • As Jump's trading style has evolved, the team has brought in new alternative datasets.