Junior Quantitative Analyst, Risk & Quant Analytics

Polymer Capital Taiwan; Hong Kong; On-site; HKD 300,000 - 600,000; Full time

Benefits offered by this job

Paid annual leave

Medical group insurance

Monthly gym subsidy / gym facility

Job summary

Polymer Capital Management in Hong Kong is seeking a highly motivated Junior Quantitative Analyst to support equity research and model development. You will apply your coding and machine learning background to build and test quantitative strategies.

Ideal candidates have a quantitative degree, strong Python skills (pandas/NumPy), and an ability to work in a fast-paced team. Fresh graduates are encouraged to apply, with less than two years of experience.

Qualifications

• Bachelor's or Master's degree in a quantitative field.
• Strong coding and ML/deep learning background.
• Familiarity with equity markets and financial instruments.
• Proficient in programming languages and data analysis libraries.

Responsibilities

• Collaborate with traders to develop quantitative models and strategies.
• Conduct research on equity market factors and risk management.
• Apply statistical and ML techniques to large datasets.
• Develop and maintain tools for data collection, cleaning and analysis.
• Monitor market trends and events affecting equity markets.

Skills

Quantitative background

Coding skills

ML knowledge

Pandas/NumPy

Teamwork

Communication

Education

Bachelor/Master in Math/Stats/CS

Tools

Python

Pandas

NumPy

Job description

Company IntroductionPolymer Capital Management is a market-neutral, multi-manager investment platform based in and focused on Asia. Polymer combines established institutional support and deep knowledge of local financial markets with a dedication to discovering and developing the region's best investment talent. Polymer was established in conjunction with PAG, one of the world's largest Asia-focused alternative asset managers, in 2019.

We are seeking a highly motivated and talented individual to join as a Junior Quantitative Analyst with a passion for equity markets. In this role, you will be responsible for applying your strong coding and machine learning academic background to support quantitative research and analysis efforts within our firm.

Job Responsibilities

• Collaborate with senior traders to develop and implement quantitative models and strategies for equity and financing/Delta 1 markets.
• Conduct research on various equity market factors and risk management.
• Utilize statistical and machine learning techniques to analyze large datasets and extract meaningful insights.
• Develop and maintain software tools and infrastructure for data collection, cleaning, and analysis.
• Monitor and analyze market trends, news, and events that may impact equity markets.

Requirements

• Bachelor's or Master's degree in a quantitative discipline such as Mathematics, Statistics, Computer Science, or a related field.
• Strong academic background in coding and machine learning and deep learning techniques.
• Knowledge of equity markets, including familiarity with market data and financial instruments.
• Proficiency in programming languages.
• Experience with data analysis and manipulation using libraries such as pandas, NumPy, or similar.
• Strong analytical and problem-solving skills, with attention to detail.
• Excellent written and verbal communication skills.
• Ability to work in a team-oriented, fast-paced environment.
• Less than 2 years of relevant work experience, fresh graduates are encouraged to apply.

Why join us?

• Prime Location: You'll work full time from our centrally located office space in the heart of Hong Kong
• High-Growth: We have a team of highly ambitious professionals with a strong desire to learn and develop their skills.
• Equal opportunity employer: We celebrate diversity and are committed to creating an inclusive environment for all employees.
• Global exposure: With six offices and three affiliate offices around the region, Polymer teams work together to solve meaningful problems at scale.

Some of our Benefits

• Paid annual leave
• Medical group insurance
• Monthly gym subsidy / gym facility