Nathaniel Ahy
MSC, Financial Mathematics
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https://www.linkedin.com/in/n
athaniel-ahy-/
Summary
Education
Proactive financial mathematics
graduate seeking to make an impact
in the excitingly innovative world of
data driven businesses. Motivated by
my curiosity, I managed to complete
my master’s degree with 130% the
required credits, nearly half of which
were in data science related fields.
My dissertation combined my
aptitude for data science and
financial mathematics by amending
the Nobel prize winning Black—
Scholes model and reducing its error
rate in data-fitting from 9% to 0.7%.
MSC | 2018--2020 | Uppsala University
https://github.com/No
tNathaniel/My-projects
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Master’s Degree in Financial Mathematics
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Strenuously studied the fundamentals of data science
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Applied statistical methods and probability theory to price
financial derivatives
BSC | 2015--2018 | Malardalens University
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Degree in Applied Mathematics specializing in Financial
Engineering
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Among 4 out of the original 50 students to complete the Financial
Engineering track
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Adopted an analytical thought process shaped by the rigors of
mathematics
Skills
Relevant Courses
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Seasoned user of Python,
MATLAB, C, and Microsoft Office
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Skilled in Java, SAS, SQL, and R
Statistical and Probabilistic Machine Learning
• Created song, credit, and sports predictors alone during spare
time and in school projects with teams using machine learning
approaches achieving 70-97% accuracy
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Proficient with PyTorch, logistic
and Bayesian regression, neural
networks, sampling, and many
more data analyst methods
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Deeply experienced in statistical
and mathematical modeling
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Fluent in English (CAE
diploma) and Swedish
Methods of Statistical Inference
• Conducted hypothesis (A/B) testing, derived confidence
intervals, applied ANOVA and maximum likelihood estimators
Database Design
• Constructed easily accessible databases by reducing redundancy
• Wrote complex SQL-queries to access relevant datasets
Analysis of Time Series
• Fit time series processes to securities data with R
• Applied statistical models to forecast time series
