Data Science Professionals - Systematic Data Platform

Millennium; Hong Kong; On-site; HKD 420,000 - 660,000; Full time

Job summary

The Systematic Data Group is building a world class systematic data platform to power the next generation of systematic portfolio engineers. The role supports onboarding and validation of datasets, performs data quality checks, and generates descriptive statistics and quality metrics for users across quantitative investing teams.

Candidates bring strong Python skills, SQL knowledge, and an eye for detail. Recent graduates and those with up to 6 years in data operations or analytics are

Qualifications

• Bachelor's degree in Computer Science, Mathematics, Statistics or related field.
• Recent graduates welcome; up to 6 years in data ops, analytics, financial data, tech or financial services.
• Strong programming skills in Python; knowledge of Go, Rust, R, Java, C#, or C++ is a plus.

Responsibilities

• Onboard, validate, and maintain internal and external datasets used across systematic investment workflows.
• Perform data quality checks, reconciliation, and root-cause analysis.
• Generate statistics, summaries, coverage reports, and quality metrics for datasets.

Skills

Python

Analytical skills

Communication

Team collaboration

Education

Bachelor's degree in CS/Math/Stats

Master's degree in CS/Math/Stats

PhD in quantitative field

Tools

Go

Rust

R

Java

C#

C++

Job description

The Systematic Data Group is building a world class systematic data platform, which will power the next generation of systematic portfolio engineers. We are looking for exceptional talents to join our growing data platform team. The team consists of content specialists, data scientists, data analysts, data operations analysts and engineers who are responsible for discovering, maintaining and analyzing sources of alpha for our portfolio managers.

This is an opportunity for individuals who are passionate about quantitative investing. The role builds on individual’s knowledge and skills in four key areas of quantitative investing: data, statistics, technology and financial markets.

What You’ll Do

• Support the onboarding, validation, and maintenance of internal and external datasets used across systematic investment workflows
• Perform data quality checks, exception handling, reconciliation, and root‑cause analysis
• Generate descriptive statistics, data summaries, coverage reports, and quality metrics to help users understand dataset characteristics
• Maintain metadata, tagging, documentation, data dictionaries, and operational runbooks for datasets and workflows
• Work with vendors and brokers to understand data characteristics, formats, definitions and quality issues
• Partner with portfolio managers to support dataset usage, data recommendation and resolve trading critical data‑related issues
• Help improve operational processes by identifying automation opportunities, workflow enhancements, and monitoring improvements
• Monitor daily data pipelines, investigate issues, and coordinate timely resolution with engineering, vendors, and internal stakeholders

What You Bring

• Bachelor’s, Master’s, or Ph.D. in Computer Science, Mathematics, Statistics or other field requiring quantitative analysis
• Recent graduates are welcome, as are candidates with up to 6 years of experience in data operations, data analytics, financial data, technology, or financial services
• Strong programming skills in Python; experience with Go, Rust, R, Java, C#, or C++ is a plus
• Strong SQL skills, including experience with SQL, PL/SQL, T‑SQL, or similar relational database technologies
• Strong analytical and problem‑solving skills, with high attention to detail and ability to investigate data issues
• Strong written and verbal communication skills, with the ability to collaborate across technical and business teams
• Solid understanding of financial data concepts, including standards, types, data lineage, normalization, and data quality