Open to opportunities

Aryan Sirsavkar

@aryansirsavkar

Early-career quantitative modeller blending machine learning, time-series research, and production engineering for systematic trading and automation.

India

Message

What I'm looking for

I’m looking for a role where I can build statistically rigorous, production-grade models—mixing quantitative finance and ML—then validate them with careful backtesting and real-time systems that reward strong engineering discipline.

I’m a quantitative modelling apprentice working in production environments, focused on building rigorous, look-ahead-free pipelines for systematic trading. I develop trading signals using probabilistic and statistical ideas while keeping evaluation transaction-cost-aware and testable.

Across my experience, I’ve combined ML and statistical modelling with real-world constraints—improving anomaly detection accuracy by 82%, and deploying models to field production. I also lead UAV automation efforts, integrating Kalman filter-based sensor fusion, probabilistic state estimation, and real-time object detection for disaster-response missions.

My research and accepted papers reflect my drive to connect theory to measurable outcomes: regime-switching frameworks for structural persistence, and robust control/perception loops for intelligent incident resolution in DevOps pipelines. I’m motivated by systems that are both statistically defensible and engineered to run reliably.

Experience

Work history, roles, and key accomplishments

Current

Quantitative Modelling Apprentice

Current

La Dolce Vita QF

Apr 2025 - Present (1 year 1 month)

Built a tick-level order management system in C++ using RabbitMQ/ZeroMQ to distribute real-time market data and route orders. Developed a causal mean-reversion signal pipeline for index derivatives and FX, deploying production Linux systems that achieved 85% directional accuracy in live investment cycles.

C++RabbitMQ ZeroMQ Linux Tick Level Order Management Causal Signal Engineering Look Ahead Free Backtesting

Current

Automation Lead — UAV Systems

Current

Team Squadrone

Mar 2024 - Present (2 years 2 months)

Led the UAV automation stack for disaster-response missions, implementing Kalman filter-based sensor fusion and probabilistic state estimation with real-time object detection. Earned All India Rank 11 overall and Rank 6 in Automation at SAE Aerothon 2025.

Sensor Fusion Kalman Filter Sensor Fusion State Estimation Object Detection Real Time Perception System Integration

ML & Anomaly Detection Intern

Data Acquisition Technologies

Jan 2025 - Apr 2025 (3 months)

Developed machine learning models for Knorr Bremse truck braking diagnostics, improving anomaly detection accuracy by 82% versus a baseline rule-based system. Managed real-world data quality issues (sensor misalignment and distribution shift) and deployed models into field production.

Machine Learning Anomaly Detection Data Quality Engineering Sensor Misalignment Handling Distribution Shift Handling Model Evaluation

Education

Degrees, certifications, and relevant coursework

University of Manchester

Master of Science, Quantitative Finance

2026 - 2027

Activities and societies: Relevant coursework: Stochastic Calculus for Finance; Time Series Econometrics; Asset Pricing Theory; Derivative Securities; Numerical Methods for Finance; Computational Finance; Statistical Modelling; Optimization Methods.

Expected MSc in Quantitative Finance focused on stochastic processes, econometrics, asset pricing, derivatives, and optimization for finance.

Savitribai Phule Pune University

Bachelor of Engineering, Mechanical Engineering

2022 - 2026

Grade: CGPA 8.09/10 (Sem 6: 8.52/10)

Activities and societies: Honors in Artificial Intelligence & Machine Learning. Relevant coursework: Probability & Statistics; Numerical & Statistical Methods; Control Systems; Machine Learning; Data Structures & Algorithms.

Pursuing a B.E. in Mechanical Engineering with honors in Artificial Intelligence & Machine Learning. Completed coursework in probability and statistics, numerical methods, control systems, and machine learning.