Quantitative Researcher/Analyst Career Guide

The brains behind a quant trading desk

Often used interchangeably, “Quantitative researcher” and “Quantitative analyst” largely mean the same thing. It is the most versatile of all quant roles with many businesses seeking such professional quants who can use mathematical and statistical methods in finance and investment management.

The role of a quant researcher often changes depending on the business. While the core role of quant researchers revolves around model development and data analysis, the specifics vary across industries, from wealth management in family businesses to speed optimization in HFTs. Programs like EPAT provide essential skills like statistical modeling, programming, and financial knowledge, making them valuable for these roles.

As you can see, the quant researcher role is one the most versatile roles in the financial markets technology sector. Other businesses that also seek quant researchers are not covered above such as equity research houses, fund management, and buy/sell side firms.

While the core job requirements for quant researchers across various businesses are largely similar, there are slight differences in the specific skills needed for each role. We will discuss this in the section below.

Quant Researcher Job Description

Can you guess which business type would have raised the following job description for a Quantitative Researcher role?

Objectives

• Conduct research and statistical analyses in the evaluation of securities
• Work with large data sets, including unconventional data sources, to predict and test statistical market patterns
• Conceptualize valuation strategies, develop and continuously improve mathematical models, and translate algorithms into code
• Back-test and implement trading models and signals in a live trading environment

Skills and Preferred Qualifications

• Advanced training in mathematics, statistics, physics, computer science, or another highly quantitative field
• Proficiency in probability & statistics (e.g. time-series analysis, machine learning, pattern recognition, NLP)
• Prior experience working in a data-driven research environment
• Hands-on programming experience in scripting (e.g. Python), analytical packages (e.g. R, Matlab) and/or compiled languages (e.g. C++)
• A background demonstrating strong analytical problem-solving skills
• An ability to communicate advanced concepts in a concise and logical way
• Proficiency in creating and using algorithms to meticulously investigate and work through large data or error-checking problems

Yes, you are right. This job requirement comes from a HFT trading firm; as you can see the focus is on speed, data-driven insights, and highly technical model development.This has been taken from Job Description of Quantitative Research position in Citadel Securities.

Quantitative Analyst Job Requirements

1. Programming Proficiency:
   • Knowledge of programming languages such as Python, R, MATLAB, or C++ is essential for data analysis, backtesting strategies, and implementing algorithms.
   • Expertise in SQL and working with databases to handle large datasets is also valuable.
2. Mathematics and Statistics:
   • A strong foundation in linear algebra, calculus, probability, and statistical modeling is critical for designing and analyzing quantitative models.
   • Familiarity with optimization techniques and numerical methods is a plus.
3. Financial Markets Knowledge:
   • Understanding market microstructure, trading mechanisms, and asset classes like equities, fixed income, FX, and derivatives.
4. Machine Learning and Data Science:
   • Ability to use ML models for predictions, sentiment analysis, or portfolio optimization.
   • Familiarity with tools like TensorFlow or PyTorch is advantageous.
5. Data Handling:
   • Competence in processing, cleaning, and analyzing large datasets from diverse sources.
   • Experience with tools like Pandas, NumPy, and big data platforms (e.g., Hadoop, Spark).
6. Soft Skills:
   • Strong problem-solving ability.
   • Communication skills for conveying complex concepts to non-technical stakeholders.

Is Programming Necessary? What if I am not from a Mathematics/Quantitative background?

Quantitative Analyst Salary New York

In accordance with New York City’s Pay Transparency Law, the base salary range for this role is $250,000 to $350,000. Base salary does not include other forms of compensation or benefits. - Citadel website

According to Glassdoor:
The estimated total pay for a Quantitative Analyst is $284,421 per year in the New York City, NY area, with an average salary of $155,062 per year. These numbers represent the median, which is the midpoint of the ranges from our proprietary Total Pay Estimate model and based on salaries collected from our users. The estimated additional pay is $129,359 per year. Additional pay could include cash bonus, commission, tips, and profit sharing.

Quantitative Analyst Salary India

A simple search on Glassdoor will show you a large variation in the salary of the quant analyst role, anything between 7 Lac pa to 70 Lac pa. Additional pay could include bonuses and profit sharing as well.

Checkout the list of Quant trading firms in India, UK & USA.

Difference between Quant Trader and Quant Analyst

The main difference between a quant trader and a quant analyst lies in their focus:

• A quant trader executes strategies in live markets and makes real-time trading decisions.
• A quant analyst focuses on researching and developing strategies by identifying new opportunities and spotting inefficiencies in the market.

In short, traders apply strategies while analysts create them.

Different quant roles in an algorithmic trading firm are summarized in the table below. Read this article on quant roles and different firms which hire quants.

I don’t have an engineering/IT degree.

Can I Become a Quant without a programming background?

Although knowledge of a programming language is necessary for most quantitative research roles, you can still start a career as a Quant without solid programming skills. We strongly recommend strengthening your coding skills to grow in your career. Programming is used to:

• Automate data analysis and strategy testing.
• Implement models for backtesting and optimization.
• Interact with APIs for real-time data and trading executions.

The ability to efficiently test and refine quantitative strategies is limited without programming skills.

Without programming knowledge, recommended Financial Markets roles for you are:

• Quantitative Analyst with a focus on strategy design or statistical analysis
• Financial Data Analyst
• Risk Manager

Businesses to Target:

• Data & Analytics Firms: Providing tools for market insights or assisting in developing visual data dashboards.
• Hedge Funds: Strategy design or risk modeling roles that rely on statistical software (e.g., MATLAB, Excel) over programming.
• Family Trading Businesses: Focus on wealth management strategies with minimal coding.

These roles allow learning programming on the job or leveraging pre-built software for analysis.

I don’t have a Math/Quant degree.

Can I Become a Quant without a degree in Math, Stats, Physics, or Computer Science?

While formal degrees in these areas provide a strong foundation, they are not strictly mandatory. Here's how you can succeed without them:

• Self-Learning: Many online courses and certifications can provide practical training
• Practical Skills: Focus on programming, data analysis, and understanding financial markets.
• Hands-On Experience: Engage in projects, internships, or competitions like Kaggle to demonstrate your capability.

With determination and the right resources, transitioning into a quantitative research role is achievable without advanced academic qualifications in traditional fields. However, bridging the gap with certifications and focused learning is crucial.

How EPAT & Quantra Prepares You

One of the benefits of choosing this career path is the career flexibility it offers. You would have opportunities to transition into quantitative analysis, data science, or fintech startups. However, if you continue to stay in algorithmic trading firms, you continue to move to senior positions as per the organizational structure. Eventually, people decide to choose between these two roles, at the peak of their careers:

• Primary Focus: Algorithmic Trading, Execution Strategies, Market Microstructure.
• Key Skills Gained:
  • Python for algorithm development.
  • Backtesting and optimizing trading strategies.
  • Market data analysis and execution algorithms.
• Suitable Roles: Trading-focused positions, algo development, and roles requiring real-time execution in electronic markets.

EPAT is ideal for individuals looking to break into:

• Prop Trading
• Hedge Funds (Trading Teams)
• Algorithmic Trading Desks at Investment Banks
• Cryptocurrency Trading Firms