Quants Associate - Data Science

Job Description

Junior Data Scientist - Quantitative Analytics

What is the opportunity?

This role exists within our Quant organization to help turn large, complex datasets into clear insights that support better decision-making across the team. You'll sit within a cross-asset quant team where different members specialize in equities, municipal bonds, corporate bonds, and other asset classes. You'll develop deep expertise in one area while gaining broader exposure to how data science is applied across multiple markets.

The Junior Data Scientist will work closely with senior quants and team members to build, test and improve data-driven models that enhance pricing, risk assessment, and operational efficiency. By delivering reliable analysis and scalable tools, this role contributes to more informed strategies, improved performance, and reduced manual effort. It supports the team's broader goal of using data to drive smarter, faster, and more consistent business outcomes.
What will you do?

• Collaborate with traders, quants, and senior team members to translate business questions into data-driven solutions
• Develop and test statistical and machine learning models to support pricing, risk, and decision-making
• Analyze structured and unstructured data to identify patterns, trends, and actionable insights
• Develop specialized expertise in one asset class (such as equities, municipal bonds, or corporate bonds) while collaborating with team members working across other markets
• Monitor model performance and improve accuracy through ongoing validation and refinement
• Create clear visualizations and reports to communicate findings to both technical and non-technical stakeholders
• Assist with automating manual processes to improve efficiency and scalability across workflows
• Build and maintain data pipelines to collect, clean, and organize large datasets for analysis

What do you need to succeed?

Must-have

• Master's degree in computer science, mathematics, statistics, engineering, or related quantitative field. PhD is a plus.
• Strong programming skills in Python, including experience with data analysis libraries such as Pandas and NumPy
• Hands-on experience building and evaluating machine learning models using frameworks such as scikit-learn, PyTorch, or TensorFlow
• Strong foundations in probability and statistics, including hypothesis testing and analysis techniques
• Experience working with real-world datasets and developing data-driven solutions through academic or project work

Nice-to-have

• Experience with KDB/q or familiarity with time-series databases and large-scale data systems
• Basic knowledge of SQL and working with relational databases
• Experience with Java or other object-oriented programming languages
• Interest in financial markets and curiosity about how different asset classes operate

What's in it for you?

• Work on real-world datasets and models that directly influence business decisions and outcomes
• Gain hands-on experience in machine learning and data analysis while building production-level tools
• Learn from experienced quants and team members in a collaborative and high-performing environment
• Develop deep expertise in one asset class while gaining exposure to data science applications across equities, fixed income, and other markets
• Contribute to meaningful projects that improve efficiency and reduce manual processes across the team
• Clear progression path with opportunities to take on increasingly complex projects and grow into senior technical roles
• Competitive compensation and a comprehensive benefits package supporting your overall well-being

The Expected Salary Range For The Above Position Is $110,000 - $135,000 Depending On Factors Including But Not Limited To The Candidate'S Experience, Skills, Registration Status; Market Conditions; And Business Needs. This Salary Range Does Not Include Other Elements Of Total Compensation, Including A Discretionary Bonus And Benefits Such As A 401(K) Program With Company-Matching Contributions; Health, Dental, Vision, Life And Disability Insurance; And Paid Time-Off Plan.
Rbc'S Compensation Philosophy And Principles Recognize The Importance Of A Highly Qualified Global Workforce And Plays A Critical Role In Attracting, Engaging And Retaining Talent That:
Drives Rbc'S High Performance Culture
Enables Collective Achievement Of Our Strategic Goals
Generates Sustainable Shareholder Returns And Above Market Shareholder Value

#LI-POST

Job Skills
Analytics, Computer Science, Critical Thinking, Data Science, Economic Analysis, Financial Derivatives, Financial Instruments, Machine Learning (ML), Problem Solving, Python (Programming Language), Quantitative Methods, Statistics

Additional Job Details

Address:

BROOKFIELD PLACE FKA 3 WORLD FINANCIAL CENTER, 200 VESEY STREET:NEW YORK

City:

New York

Country:

United States of America

Work hours/week:

40

Employment Type:

Full time

Platform:

CAPITAL MARKETS

Job Type:

Regular

Pay Type:

Salaried

Posted Date:

2026-05-04

Application Deadline:

2026-07-24
Note: Applications will be accepted until 11:59 PM on the day prior to the application deadline date above

Our Employment Opportunities

At RBC, we are guided by living shared values of Client First, Integrity, Collaboration, Respect and Excellence and winning together as One RBC. We believe an inclusive workplace that has diverse perspectives is core to our continued growth as one of the largest and most successful banks in the world. Maintaining a workplace where our employees feel supported to perform at their best, effectively collaborate, drive innovation, and grow professionally helps to bring our Purpose to life and create value for our clients and communities. RBC strives to deliver this through policies and programs intended to foster a workplace based on respect, belonging and opportunity for all.

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RBC is presently inviting candidates to apply for this existing vacancy. Applying to this posting allows you to express your interest in this current career opportunity at RBC. Qualified applicants may be contacted to review their resume in more detail.