Quantitative Finance Career Coach

We are a North America-based career coaching firm dedicated to helping students and early-career professionals secure competitive positions at leading quantitative finance firms, hedge funds, proprietary trading firms, investment banks, and fintech companies. Our students come from top universities including CMU, Cornell, MIT, Stanford, Berkeley, Princeton, Columbia, UChicago, NYU, Waterloo, and other leading institutions. We provide personalized career coaching that includes resume development, interview preparation, networking strategy, technical guidance, and recruiting support. We are seeking experienced Quant Finance Career Coaches who have firsthand industry experience and a passion for mentoring the next generation of quantitative finance professionals. Responsibilities as a Quant Finance Career Coach, you will:

• Conduct 1-on-1 career consultations
• Evaluate students' backgrounds and identify strengths and gaps
• Develop customized recruiting roadmaps
• Help students target appropriate firms and roles

Examples include

• Quant Research
• Quant Trading
• Quant Developer
• Quantitative Analyst
• Risk Quant
• Systematic Trading
• Algorithmic Trading
• Portfolio Analytics

Resume & LinkedIn OptimizationGuide students in

• Quant-focused resume writing
• Technical storytelling
• Research presentation
• Project positioning
• GitHub optimization
• LinkedIn branding

Technical Interview PreparationCoach students on:Mathematics

• Probability
• Statistics
• Linear Algebra
• Optimization
• Stochastic Processes

Programming

• Python
• C++
• SQL
• Data Structures
• Algorithms

Quant Topics

• Options
• Derivatives
• Portfolio Theory
• Market Microstructure
• Time Series
• Machine Learning
• Factor Models

Mock InterviewsConduct realistic mock interviews including

• Technical interviews
• Quant brainteasers
• Probability questions
• Coding interviews
• Behavioral interviews
• Research discussions

Provide detailed feedback and improvement plans.Recruiting SupportAdvise students on:

• Internship recruiting
• Full-time recruiting
• Networking strategy
• Referral strategy
• Recruiting timelines
• Offer negotiation

Student Mentorship

• Track student progress
• Assign weekly action items
• Review applications
• Support recruiting throughout the hiring cycle
• Provide motivation and accountability

Required Qualifications

• Bachelor's degree in:
• Mathematics
• Statistics
• Computer Science
• Physics
• Financial Engineering
• Operations Research
• Economics
• Quantitative Finance
• Related quantitative discipline

Preferred:Master's or PhDProfessional ExperienceMinimum 3+ years in one or more of the following:

• Quant Research
• Quant Trading
• Quantitative Development
• Quantitative Risk
• Systematic Investing
• Portfolio Analytics
• Financial Engineering
• Algorithmic Trading

Experience at leading firms is highly preferred.Technical SkillsStrong knowledge of:Programming

• Python
• C++
• SQL

Quantitative Topics

• Probability
• Statistics
• Machine Learning
• Time Series
• Derivatives
• Optimization
• Numerical Methods

Recruiting KnowledgeDeep understanding of recruiting at

• Hedge Funds
• Proprietary Trading Firms
• Investment Banks
• Asset Managers
• FinTech Companies

Knowledge of

• OA assessments
• Quant interviews
• Coding interviews
• Brainteasers
• Research presentations
• Hiring timelines

Coaching SkillsExcellent ability to

• Explain complex concepts clearly
• Mentor students with diverse backgrounds
• Deliver actionable feedback
• Build confidence
• Communicate professionally

Preferred QualificationsExperience with

• ACM/ICPC
• Kaggle
• Putnam
• Math Olympiad
• Competitive Programming
• Quant competitions

Ideal CandidateYou are someone who

• Has worked in quantitative finance or systematic investing
• Understands what top firms look for in candidates
• Enjoys mentoring students
• Stays current with hiring trends and interview practices
• Can simplify advanced quantitative concepts
• Is organized, responsive, and student-focused

Pay: $40.00 - $50.00 per hour

Benefits

* Flexible schedule

Work Location: Remote