Portfolio Construction Analyst

UBIQUANT TECHNOLOGY SERVICES PTE. LTD.; Singapore; On-site; SGD 120,000 - 190,000; Full time

Job summary

UBIQUANT TECHNOLOGY SERVICES PTE. LTD. seeks a design-focused quantitative systems engineer to design and develop portfolio management systems for live trading environments.

You will manage the full lifecycle of quantitative strategies, from submission through live trading, including position tracking and trade result analysis. You will build BI dashboards to support investment decision-making and deliver data-driven insights to upstream and downstream teams across strategy types, ensuring

Qualifications

• Experience in model performance evaluation and metric design, with prior experience in strategy evaluation, backtesting, or related analytics strongly preferred.
• Proficiency in at least one programming language such as Python, MATLAB, R, or SAS, with deep understanding of data analysis libraries like pandas.
• Strong learning agility to quickly ramp up and iterate in a fast-paced financial environment.
• Research or management experience in at least one category of common quantitative strategies
• Familiarity with or hands-on experience with mainstream risk models such as Barra
• Bachelor's degree or above in a STEM discipline from a recognized institution, preferably in Mathematics, Statistics, Finance, Computer Science, Electronics, Automation, or related fields

Responsibilities

• Design and develop portfolio management systems to manage quantitative strategies from submission through live trading, including position tracking and trade result analysis
• Build topic-specific BI dashboards to support investment decision-making processes
• Deliver strategy- and trading-level data analysis to upstream and downstream teams according to varying strategy types and business needs
• Track live performance of quantitative strategies and produce regular evaluation, comparison reports, and actionable recommendations for the CIO and Investment Decision Committee
• Translate upstream business requirements into internal strategy management objectives by liaising with internal product, marketing teams, external investors, and regulators

Skills

Python

MATLAB

R

SAS

Pandas

Backtesting

Strategy evaluation

Data analysis

Learning agility

Education

Bachelor's degree in STEM

Tools

SQL

Excel

Job description

Job Summary

Design and develop portfolio management systems and manage the full lifecycle of quantitative strategies. Provide data analytics support and deliver actionable insights to support investment decisions and stakeholder requirements.

Responsibilities

• Design and develop portfolio management systems to manage quantitative strategies from submission through live trading, including position tracking and trade result analysis
• Build topic-specific BI dashboards to support investment decision-making processes
• Deliver strategy- and trading-level data analysis to upstream and downstream teams according to varying strategy types and business needs
• Track live performance of quantitative strategies and produce regular evaluation, comparison reports, and actionable recommendations for the CIO and Investment Decision Committee
• Translate upstream business requirements into internal strategy management objectives by liaising with internal product, marketing teams, external investors, and regulators

Preferred competencies and qualifications

• Experience in model performance evaluation and metric design, with prior experience in strategy evaluation, backtesting, or related analytics strongly preferred
• Proficiency in at least one programming language such as Python, MATLAB, R, or SAS, with deep understanding of data analysis libraries like pandas
• Strong learning agility to quickly ramp up and iterate in a fast-paced financial environment
• Research or management experience in at least one category of common quantitative strategies
• Familiarity with or hands-on experience with mainstream risk models such as Barra
• Bachelor's degree or above in a STEM discipline from a recognized institution, preferably in Mathematics, Statistics, Finance, Computer Science, Electronics, Automation, or related fields