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@silvanaacosta
Data scientist and econometrician with expertise in statistical learning.
I am a data scientist with seven years of experience across tech, finance, and consultancy, specializing in analyzing and modeling data. My proficiency in R, Python, and SQL, coupled with a Ph.D. in econometrics, allows me to develop robust models and insights from complex datasets. I have successfully led projects throughout their life cycle, collaborating with diverse stakeholders and mentoring junior data scientists.
My career has been marked by significant contributions at Activision Blizzard King, where I utilized advanced statistical techniques for A/B testing and customer segmentation, enhancing revenue forecasting and business strategies. I am passionate about making data-driven decisions accessible and understandable, often translating complex analyses into actionable insights for non-technical audiences. Additionally, my leadership roles in organizations like Women Who Code and R-Ladies reflect my commitment to fostering diversity in tech.
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Work history, roles, and key accomplishments
Activision Blizzard King
Jan 2021 - Aug 2024 (3 years 7 months)
Worked in the Central Insights Data Science Team analyzing player actions across various game titles. Utilized R, Python, and BigQuery for A/B testing, customer segmentation, and revenue forecasting. Contributed to the development of internal R packages and wrote technical reports for non-technical stakeholders.
UBS
Jul 2020 - Nov 2020 (4 months)
Led validation projects for Anti-Financial Crime Models within the AI Monitoring & Surveillance Models Validation Team. Conducted model assessments, developed alternatives, and documented processes while supervising another data scientist.
NASDAQ
Apr 2019 - Jul 2020 (1 year 3 months)
Worked in the Risk Modeling Team, implementing dimension reduction techniques and clustering algorithms for clearing derivatives. Analyzed intra-daily data and performed automatic reporting and data visualizations.
CREATES, Aarhus Universitet
Sep 2013 - Sep 2018 (5 years)
Conducted simulations and developed mathematical results connecting discrete and continuous-time processes. Focused on high-frequency volatility estimation and worked in interdisciplinary teams.
Department of Economics, Aarhus Universitet
Sep 2015 - Aug 2016 (11 months)
Planned and presented tutorials in econometrics, leading discussions on multiple regression models and various econometric techniques for groups of students.
Instituto de Economía (IECON), Universidad de la República
Jul 2008 - Jul 2011 (3 years)
Assisted in writing macroeconomic reports and assembling datasets for analysis. Conducted forecasting analysis using various econometric methods.
Deloitte
Mar 2008 - Jul 2008 (4 months)
Worked as a junior analyst in the Economic Analysis Team, updating international finance datasets and contributing to reports for clients.
Degrees, certifications, and relevant coursework
Ph.D. in Economics, Economics
2013 - 2018
Conducted research on estimating spot and integrated variance, covariances and betas of continuous-time Itô semi-martingales, both with parametric and non-parametric methods. CREATES is ranked in 2018 by IDEAS RePEc in the world’s top 4 in the field of Time-Series Econometrics.
M.Sc. in Economics, Economics
2013 - 2015
Relevant Coursework: Measure Theory, Real Analysis and Probability, Probability Theory, Markov Chains, Mathematical Analysis, Advanced Financial Econometrics, High-Frequency Econometrics, and Modeling and Forecasting Volatility.
M.A. in Economics, Economics
2011 - 2013
Relevant Coursework: Microeconomics, Macroeconomics, and Econometrics. Specialized courses included Industrial Organization and Contract Theory.
B.A. in Economics, Economics
2007 - 2011
Ranked in the top 5% of my class and wrote my thesis on a Markov regime switching GARCH model for FX data.
Software and tools used professionally
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