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Career β†’ Experience β†’ Started ML Consulting Practice

Started ML Consulting Practice

Launched independent consulting practice focused on machine learning applications in quantitative finance and risk management.

Started ML Consulting Practice

πŸš€ New venture! Excited to announce the launch of my independent consulting practice specializing in machine learning applications for quantitative finance!

Consulting Practice Overview

Practice Name: QuantML Solutions

Focus Areas: Machine Learning, Quantitative Finance, Risk Management

Target Clients: Hedge funds, asset managers, fintech startups, and traditional banks

Service Offerings

Algorithm Development

  • Trading Strategy Development: Custom ML algorithms for systematic trading
  • Risk Model Construction: Advanced risk models using ensemble methods
  • Portfolio Optimization: Multi-objective optimization with ML constraints
  • Market Prediction: Time series forecasting with deep learning

System Implementation

  • Production Deployment: Converting research models to production systems
  • Performance Optimization: Low-latency implementations for real-time trading
  • Infrastructure Design: Scalable ML infrastructure for financial applications
  • Integration Services: Connecting ML systems with existing trading platforms

Research and Analysis

  • Strategy Backtesting: Comprehensive historical validation of trading strategies
  • Alternative Data Integration: Incorporating satellite imagery, social media, news sentiment
  • Regulatory Compliance: Ensuring ML models meet regulatory requirements
  • Model Validation: Independent validation of existing quantitative models

Why Start Consulting?

Market Opportunity

Growing demand for:

  • AI Transformation: Traditional firms needing ML expertise
  • Specialized Knowledge: Intersection of ML and finance expertise
  • Independent Validation: Third-party model validation and risk assessment
  • Rapid Innovation: Startups needing quick time-to-market solutions

Personal Motivation

  • Knowledge Sharing: Applying experience from IB to broader market
  • Innovation Freedom: Exploring cutting-edge techniques without corporate constraints
  • Impact Diversity: Working across different types of financial institutions
  • Entrepreneurial Challenge: Building business alongside technical expertise

First Client Projects

Hedge Fund Risk System

Client: Mid-size quantitative hedge fund

Challenge: Real-time portfolio risk monitoring across 5,000+ positions

Solution:

  • Distributed ML system for real-time VaR calculation
  • Custom GPU-accelerated Monte Carlo simulations
  • Integration with existing portfolio management system

Impact: 85% reduction in risk calculation time, enabling intraday rebalancing

Cryptocurrency Trading Platform

Client: Fintech startup entering crypto markets

Challenge: Building market making algorithms for volatile crypto markets

Solution:

  • Reinforcement learning agent for optimal bid/ask placement
  • Multi-exchange arbitrage detection system
  • Dynamic inventory management with volatility adjustment

Impact: 40% improvement in profitability vs. traditional market making

Bank Capital Allocation

Client: Regional bank optimizing loan portfolio

Challenge: Dynamic capital allocation across loan types and regions

Solution:

  • Ensemble models predicting default probabilities
  • Multi-objective optimization balancing risk, return, and regulatory capital
  • Stress testing framework for economic scenario analysis

Impact: 15% improvement in risk-adjusted returns while maintaining regulatory compliance

Technical Differentiation

Unique Value Proposition

Combining:

  • Academic Rigor: MS degrees in CS and Quantitative Finance
  • Industry Experience: Production systems at major broker
  • Research Background: Published papers and patent applications
  • CFA Charter: Comprehensive investment management knowledge

Technical Expertise

  • Low-Latency Systems: Microsecond-level optimization techniques
  • Financial Mathematics: Advanced derivatives pricing and risk models
  • Machine Learning: Deep learning, reinforcement learning, ensemble methods
  • Infrastructure: Distributed systems, GPU computing, cloud deployment

Business Development

Client Acquisition

Building client base through:

  • Industry Networks: Connections from Interactive Brokers and Georgia Tech
  • Conference Speaking: Presentations at QuantCon and similar events
  • Academic Collaboration: Joint research projects leading to consulting opportunities
  • Referral Programs: Satisfied clients referring similar organizations

Partnership Strategy

  • Technology Vendors: Partnering with trading platform providers
  • Academic Institutions: Collaborating with university research labs
  • Legal Firms: Working with attorneys on regulatory compliance
  • Accounting Firms: Partnering on model validation services

Operating Model

Time Management

Balancing consulting with full-time role:

  • Evening/Weekend Work: Client projects during off-hours
  • Vacation Consulting: Using PTO for intensive project phases
  • Remote Delivery: Leveraging technology for efficient client service
  • Team Expansion: Planning to hire additional consultants

Quality Assurance

  • Code Review Process: Rigorous testing and validation procedures
  • Documentation Standards: Comprehensive technical documentation
  • Performance Monitoring: Ongoing monitoring of deployed systems
  • Client Communication: Regular progress updates and technical briefings

Future Vision

Practice Growth

  • Team Expansion: Hiring 2-3 additional consultants within 18 months
  • Specialization: Developing specific expertise in crypto and alternative assets
  • Product Development: Creating standardized ML tools for financial applications
  • International Expansion: Serving clients in European and Asian markets

Industry Impact

  • Best Practices: Establishing standards for ML in finance
  • Open Source: Contributing tools and frameworks to open source community
  • Education: Teaching courses on ML applications in quantitative finance
  • Research: Publishing applied research bridging academia and industry

Personal Reflection

Starting a consulting practice represents the natural evolution of my career - from learning ML and finance, to applying them in production, to now helping others leverage these powerful combinations.

This venture allows me to share knowledge, solve diverse problems, and contribute to the broader adoption of responsible AI in financial markets.

From employee to entrepreneur - the next chapter begins! πŸ’ΌπŸ€–

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Career Update

November 30, 2024