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Valentina Torres da Silva

@valentinatorresdasil

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I'm a machine learning engineer building reliable, bias-aware data products and research pipelines.

United States

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What I'm looking for

I'm looking to build accountable machine learning and data products, especially where rigorous research, model governance, and real-world impact intersect.

At Women in Data Science Worldwide, I built a three-model pipeline for WiDS Elevate spanning propensity scoring, fraud detection, and P&L stress simulation. I achieved a 71.6% fraud catch rate across 45K shadow transactions and helped launch the 2026 WiDS Global Datathon on wildfire risk.

As a Columbia Data Science Institute Scholar, I'm building resilient web-scraping pipelines and structured research databases for measuring ideological change in American universities. My work uses Python, Playwright, BeautifulSoup, Scrapy, PostgreSQL, and SQLite to make archive data queryable across institutions, keywords, and dates.

I've also developed a RAG application for legal-contract extraction, built a NOAA-funded river-ice classification pipeline, and led an award-winning hackathon team. I care about model governance, structural bias, and turning complex data into practical, accountable systems.

Experience

Work history, roles, and key accomplishments

Current

DSI Scholar Researcher

Current

Columbia University Data Science Institute

Sep 2026 - Present (1 month)

Selected as a DSI Scholar for Measuring Ideological Change in American Universities, building a web-scraping pipeline with error handling, checkpointing, and logging. Designing a structured PostgreSQL/SQLite database to support querying by institution, keyword, and date range.

Python Playwright BeautifulSoup Scrapy PostgreSQL SQLite Web Scraping Data Pipelines Database Design

Researcher

Fairleigh Dickinson University

Dec 2025 - Jun 2026 (6 months)

Developed a NOAA-funded VIIRS pipeline using sub-pixel water-fraction features derived from Landsat surface data to classify river ice on narrow Alaskan rivers, achieving 0.781 cross-validation accuracy on 178 visually confirmed pixels.

Remote Sensing VIIRS LANDSAT Geospatial analysis Machine Learning Python

Teaching Assistant

Fairleigh Dickinson University

Jan 2026 - May 2026 (4 months)

Graded homework and exams for a class of more than 50 graduate and undergraduate students in a Database Systems course.

Grading DataBase Systems Education

Machine Learning Engineer Intern

Women in Data Science (WiDS) Worldwide

Sep 2025 - May 2026 (8 months)

Built a 3-model ML pipeline for WiDS Elevate, a senior executive curriculum, spanning propensity scoring, fraud detection, and P&L stress simulation. Achieved 71.6% fraud catch rate (PR-AUC 0.816) across 45K shadow transactions and launched the 2026 WiDS Global Datathon on wildfire risk.

Machine Learning Python Fraud Detection Propensity Scoring Survival Analysis Data Engineering Model Governance

RAG-Enabled AI-Powered Legal Contract Data Extraction

FDU + RSG Media/ Rightsline

Aug 2024 - Nov 2024 (3 months)

Developed a Retrieval-Augmented Generation (RAG) application to automate context-aware data extraction from legal contracts at RSG Media/Rightsline, replacing manual review with near-real-time querying and earning 5/5 client feedback scores.

RAG NLP Python Legal Tech Data Extraction

Team Leader

Long Run | Battle of the Brains

Oct 2024 - Oct 2024 (0 months)

Earned Best Technology Solution award and 3rd place ($10,000 prize) at national HSI Battle of the Brains hackathon (20+ teams) by leading an 8-person team to design and pitch LONG RUN, a sustainable outdoor gear brand within 16 hours.

Leadership Pitch Hackathons Design

Education

Degrees, certifications, and relevant coursework

Columbia University

Master of Science, Data Science

Pursuing a Master of Science in Data Science with an expected graduation in December 2027.

Fairleigh Dickinson University

Bachelor of Science, Computer Science

Grade: 3.96/4.0

Activities and societies: NCAA Division I Tennis Student-Athlete

Completed a Bachelor of Science in Computer Science with a minor in Mathematics and a concentration in Big Data Analytics, graduating in May 2026 with a GPA of 3.96/4.0.