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Data Analyst
Job summary
A global finance firm in Singapore is seeking a Data Analyst to support investment teams through the analysis of financial datasets. The ideal candidate should possess strong programming skills in Python and SQL, with a passion for data and attention to detail. This full-time role is entry-level and provides a unique opportunity to contribute to a high-performing data services team.
Qualifications
- Strong programming skills in Python and SQL.
- Financial industry experience preferred but not required.
- Ability to multitask and prioritize assignments.
Responsibilities
- Analyzing financial datasets and preparing reports for investment teams.
- Creating derived data content and data ingestion pipelines.
- Defining and automating qualitative data checks.
Skills
Join to apply for the Data Analyst role at Point72
Cubist Systematic Strategies, an affiliate of Point72, deploys systematic, computer-driven trading strategies across multiple liquid asset classes, including equities, futures and foreign exchange. The core of our effort is rigorous research into a wide range of market anomalies, fueled by our unparalleled access to a wide range of publicly available data sources.
We are passionate about data. We collaborate to build elegant, effective, scalable and highly reliable solutions to empower predictive modelling in finance. Cubist’s data services group is looking for a Data Analyst to join our dedicated team. Our group is responsible for the timely delivery of comprehensive and error-free data to some of the most demanding and successful systematic Portfolio Managers in the world.
This exceptional individual will be a member of a small team of Data Scientists/Analysts who play a vital role in ensuring the smooth day‑to‑day implementation of a large research infrastructure, and the live production trading of billions of dollars of capital across global capital markets, including equities, futures, options and other financial instruments.
- Analyzing financial datasets and preparing reports for investment teams
- Creating derived data content and data ingestion pipelines
- Identifying potential data sources
- Engaging with vendors to understand characteristics of datasets
- Defining and automating qualitative data checks
- Assisting with data questions and requests from investment teams
- Creating and maintaining internal documentation on datasets
- Strong programming skills in Python and SQL. Experience with AWS and Airflow preferred but not required
- Financial industry experience preferred but not required
- Strong organization, communication and interpersonal skills
- Attention to detail and a love of process
- Strong oral and written communication skills
- Ability to exercise sound judgment in assessing and determining how to handle queries, calls and issues
- Ability to multitask and prioritize assignments
Entry level
Full‑time
Information Technology
* The salary benchmark is based on the target salaries of market leaders in their relevant sectors. It is intended to serve as a guide to help Premium Members assess open positions and to help in salary negotiations. The salary benchmark is not provided directly by the company, which could be significantly higher or lower.