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Salary: Open
Employment Type: Permanent
Sub-industry: Investment Banking
Function: Financial Services

Company Overview

Global investment management firm built at the intersection of financial theory and practical application. We strive to deliver superior, long-term results for our clients by seeking to filter out market noise to identify and isolate what matters most, and by developing ideas that stand up to rigorous testing. Underpinning this philosophy is an unrelenting commitment to excellence in technology — powering our insights and analysis.

Job Description

Job Description :

Technology has long been essential ingredient to our success, and as an Embedded Engineer in Research you will be knee-deep in mission critical challenges that make our investment ideas a reality.  Collaborating side by side with researchers and portfolio analysts, you will be responsible for designing and implementing proprietary systems and tools that drive the quantitative strategy research and systematic investing that powers the organisation. 

Your Role

As an Embedded Engineer in Research you will build or extend our:
Global asset signal, data and risk estimation infrastructure incorporating millions of data points
Intuitive research APIs leveraging cloud computing and cutting-edge visualizations
High-performance historical simulation/back testing engine for vetting new alpha strategies
Bespoke technology solutions that satisfy the needs of specific asset classes and research needs
Partner with not only local but also global team of research engineers for successful product delivery

What You’ll Bring

BS/MS/PhD in Computer Science, Computational Finance, Data Science, or related discipline
At least 5 - 11 years of experience as a quantitative developer, preferably in the financial services industry
Outstanding communication, coding, debugging, and analytical skills
Strength in pragmatic design and deploying applications using Linux/Docker/Python
An interest in quantitative finance (no finance / trading experience required)
Experience with Python / NumPy / pandas or similar quantitative stack is a plus
Demonstrated contributions to open-source software is also a plus
An aptitude for mathematics, finance and econometrics is desired

Who You Are

Mature, thoughtful, and a natural fit for a collaborative, team-oriented culture
Hard-working and eager to learn in a fast-paced, innovative environment
Committed to intellectual integrity, transparency, and openness
Motivated by the transformational effects of technology-at-scale