Languages & Tools
Python, R, SQL, LaTeX, Tableau
$ building_signal_from_noise
Data science, machine learning, and quantitative market research.
I build research systems, models, and analytics that turn messy data into decisions. My work spans machine learning, statistical modeling, market microstructure, and systematic strategy research.
matteo@portfolio:~$ load_research_profile
focus: quantitative research, ML, market analysis
recent: macro modeling, strategy research, threshold optimization
01 // about
Built for hard problems and high-signal analysis.
I’m Matteo Salinas, a quantitative analyst focused on building systematic research and trading frameworks. My work spans model development, data engineering, and market research, with an emphasis on turning raw data into structured, testable insights. I design workflows that are reproducible and scalable, from regime-based models to cross-sectional portfolio construction and options-driven strategies. I’m especially interested in problems where statistics, derivatives, and real-world decision-making intersect: forecasting, market microstructure, portfolio construction, and systematic trading.
02 // skills
Technical toolkit
Data Science
Exploratory analysis, feature engineering, preprocessing, supervised learning (regression & classification), dimensionality reduction, forecasting, model diagnostics
Quant Research
Market microstructure, volatility modeling, factor research, systematic strategy design & backtesting, execution analysis, time series modeling, data pipeline development
03 // projects
Selected work
project_01
SPY Latent-State Regime Classifier
A walk-forward allocation framework that infers market regimes from low-dimensional price behavior and dynamically adjusts exposure using a latent-state model with volatility and trend overlays. Designed to improve risk-adjusted returns through regime-aware positioning.
project_02
Dynamic Sector Allocation Strategy
A systematic, rules-based equity allocation framework that dynamically distributes capital across sectors using data-driven signals. It emphasizes consistency, robustness, and strong risk-adjusted returns while adapting to changing market environments through disciplined, sector-aware positioning.
project_03
Options Strategy Backtesting & Index Construction
An options-based equity index for medium-volatility underlyings, deployable as a strategy or index, with an automated hedge structure and disciplined capital scaling. It sources exposure through options, targeting improved risk-adjusted returns and capital efficiency via dynamic sizing and systematic hedging.
04 // experience
Experience snapshot
July 2025 - Present
Bank of America, Charlotte, NC
Quantitative Analyst · GBAM Stress Testing, Model Development Team
Builds and validates benchmark and challenger models for Global Markets revenue forecasting, evaluating regression and time-series frameworks. Developed a Global Markets Total Revenue model using thousands of macroeconomic variables, including feature engineering, preprocessing, dimensionality reduction, and model diagnostics, with a focus on robustness, interpretability, and stress sensitivity under adverse macroeconomic scenarios.
July 2024 - July 2025
Bank of America, Charlotte, NC
Quantitative Analyst · Anti-Money Laundering, Advanced Analytics Team
Designed a framework for threshold optimization, correcting logical errors and improving accuracy and population capture. Audited and refactored thousands of lines of Python and Teradata code, contributing to $6.7 million in potential cost savings, and partnered with 30+ stakeholders to diagnose and fix code issues impacting downstream processes.
June 2023 - August 2023
Global Endowment Management (GEM), Charlotte, NC
Summer Analyst
Summer Analyst at an $11B+ AUM OCIO firm. Led analysis of equity distribution timing strategies by market capitalization, comparing VWAP, TWAP, and MOC execution using statistical analysis and data visualization. Evaluated financial statements across buyout, real estate, credit, and venture capital managers, and authored an 11-page research paper on a $100M credit hedge strategy, leveraging option Greeks to enhance effective exposure without increasing capital deployed.
May 2022 - August 2022
Celonis, Raleigh, NC
Business Development Representative Intern
Conducted ad hoc data analysis projects for various teams within the office. Spearheaded a data analytics project that saved Celonis over $45 million in 2022, leading to modifications in business operations across the United States.
05 // contact
Let’s build something.
I’m interested in roles and collaborations across quantitative research, algorithmic trading, and market research.