PhD in Astrophysics · Data Analyst

Vanessa
Lorenzoni

Since I was little, I've been fascinated by the Universe and its mysteries — that's what led me to physics in 2014. Along the way, I completed a master's degree and a doctorate with a focus on astrophysics, where I worked with SQL, Python, and statistical analysis long before they were called "data skills." With my PhD done, I brought all of that into a new field — I joined a consultancy, was placed at a client company from day one as a Data Analyst, and it didn't take long before they invited me to join them directly. Along the way, I also took on the role of bringing data knowledge to non-technical teams through internal courses. Looking back, I was always a data analyst — the subject just changed.

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Vanessa Lorenzoni

Work Experience

Where I've worked

Mar 2025 — Present

Sicredi

Data Analyst — Payment Methods Team

Internalized directly into Sicredi's Payment Methods team after being allocated there through Compass UOL — one of Brazil's largest cooperative financial institutions. Working on the cards journey with a focus on credit revenue analytics, building data structures, dashboards, and analytical models using Databricks, SQL, Python etc.

Databricks SQL Python Payments Financial Data

Aug 2024 — Mar 2025

Compass UOL

Data Scientist — Allocated to Sicredi

Joined Compass UOL, a leading technology consulting firm, as a Data Scientist and was allocated to Sicredi's Payments Ways team from day one. Worked embedded within the client's data team for 7 months, contributing to the same analytical and pipeline work — earning a full-time offer to join Sicredi directly.

Consulting Databricks SQL Python Data Science

Education

Academic background

Bachelor of Science

Physics

Universidade Federal de Santa Maria

UFSM · Brazil · 2015

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Master of Science

Physics

Universidade Federal de Santa Maria

UFSM · Brazil · 2019

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Doctor of Philosophy

Physics — Extragalactic Astrophysics

Universidade Federal de Santa Maria

UFSM · Brazil · 2024

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Specialization · In Progress

Data Science

Ongoing

Current

Peer-Reviewed Publication

Monthly Notices of the Royal Astronomical Society

Volume 527, Issue 2
pp. 3542–3558
January 2024

DOI: 10.1093/mnras/stad3435
arXiv: 2311.01577

Probing Stellar Populations and Interstellar Medium in Early-Type Central Galaxies

Analysis of stellar populations and the interstellar medium (ISM) in 15,107 early-type central galaxies from the SPIDER survey using SDSS optical spectra. The study investigates stellar age, metallicity, visual extinction, and Hα equivalent width — exploring how these properties relate to central velocity dispersion and halo mass across isolated and group central galaxies. Proposes a scenario where ionized gas properties are shaped by AGN feedback and intracluster medium cooling.

Extragalactic Astrophysics Stellar Populations SDSS AGN Feedback Galaxy Evolution

Skills

Technical proficiency


How I work

01

Analytical Thinking

After 12 years in exact sciences and astrophysics, breaking down complex problems step by step just became how I think. It carried over naturally into data work.

02

Communication

Presenting research and data findings to very different audiences, from academic committees to business teams, made communication feel natural over time. I'm always looking to improve, but it's something that flows easily when the moment asks for it.

03

Adaptability

Going from astrophysics to financial data analysis wasn't an obvious path — but it worked. I adapt when I need to, even if the beginning of something new takes a little longer. New challenges don't scare me.

04

Curiosity

Curiosity is just part of who I am — it's what made me fall in love with the cosmos as a kid and end up studying physics. As a data analyst, it's what makes me actually enjoy the work. I genuinely want to know what's hiding in the data.

05

Collaboration

I've always worked alongside people from different backgrounds — researchers, physicists, and now developers, PMs, data engineers, architects. Having different perspectives on the same problem is something I genuinely value. You always come out with a richer view of things.

06

Attention to Detail

In astrophysics, the data doesn't forgive careless mistakes — and neither does a financial pipeline. Working in both worlds made me naturally careful with the details, because one small error can change the whole picture.

Certificates & Courses

Continuous learning

02

Advanced Learning Algorithms

DeepLearning.AI — Coursera

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03

Unsupervised Learning, Recommenders & Reinforcement Learning

DeepLearning.AI — Coursera

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04

Santander Bootcamp 2023 — Backend Java

Santander / DIO

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05

Master SQL for Data Science

Udemy

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06

Lei Geral de Proteção de Dados (LGPD)

Brazil — Data Privacy

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07

Desenvolvimento Orientado a Objetos

Object-Oriented Programming

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Languages

How I communicate

Português
Native Full professional proficiency
English
Intermediate Professional working proficiency

Let's connect

Open to new opportunities in data analytics, especially in global or remote roles. Fluent in data — learning every day to be more fluent in English.