Skills
Programming & Tools
Python
R
SQL
HTML
Database & Cloud
PostgreSQL
MongoDB
AWS EC2
AWS Lambda
Supervised Machine Learning
Linear Regression
Logistic Regression
Naive Bayes
K-Nearest-Neighbors (KNN)
Decision Trees
Random Forest
Support Vector Machines (SVM)
Unsupervised Machine Learning
K-Means Clustering
Hierarchical Agglomerative Clustering
DB-SCAN
Natural Language Processing (NLP)
Topic Modeling
Singular Value Decomposition (SVD)
Principal Component Analysis (PCA)
Python Packages
Pandas
NumPy
Scikit-Learn
BeautifulSoup
Selenium
PyMongo
PDFMiner
Data Visualization
Matplotlib
Plotly
Tableau
Folium
Education
University of Texas at Austin
Fall 2013 - Spring 2017
B.B.A. Finance (Business Honors Program)
GPA: 3.77; ACT: 35
Alexander Parker
Experience
Metis
Chicago, IL
Data Scientist
Summer 2019

  • Metis is an accredited 12­-week immersive data science bootcamp focused on Python, statistics, supervised and unsupervised machine learning, data analysis, visualization techniques and database management
  • Designed five end-to-end projects utilizing data acquisition, cleaning and modeling to derive data­-driven insights
  • Presented results to technical and nontechnical audiences
Metis Projects

StarCraft opponent strategy prediction via a bayesian programming model

  • Developed a custom model to memorize player decisions from StarCraft game replays in a tree data structure with important attributes such as decision timing and decision frequency from the memorized game replays
  • Designed an algorithm to detect decision nodes affected by an in-game observation and to update the probabilities of those nodes with Bayes Theorem. Probability changes are then propagated to all other nodes
  • Extracted in-game observations and opponent decisions from a MySQL database containing 5,000+ game replays in a frame-by-frame format

NLP and topic analysis of Youtube-recommended videos

  • Built AWS-hosted MongoDB database and AWS Lamba pipeline to webscrape youtube video recommendations
  • Utilized youtube data API to find video captions and generated tokenized, vectorized data for each video
  • Created topic modeling algorithm to evaluate shift in topic and tone over video recommendations

Oil and gas spill severity classifier

  • Utilized logistic regression model to analyze significant predictors of oil and gas spill severity
  • Structured PostgreSQL database to manage 5+ years of Colorado public oil and gas spill filings
  • Developed hyper parameter-tuning functions for KNN, logistic regression, naive bayes, SVM, decision tree and random forest models

Hydraulic fracturing fluid mixture and well performance uplift estimator

  • Webscraped PDF forms using the BeautifulSoup package and extracted import text with the PDFMiner package
  • Built linear regression model to predict initial well production utilizing Lasso and Ridge regularization techniques

Jefferies
Houston, TX
Investment Banking Analyst
Summer 2017 - Spring 2019

  • Provided M&A and financing advice to upstream and midstream companies in the domestic oil and gas space
  • Contributed to all stages of financial transactions including strategic discussions, valuation and process execution

Select Transaction Experience

Sell-side advisor to Penn Virginia Corporation on its proposed ~$1.7B sale to Denbury Resources

  • Engaged by the company to explore strategic alternatives such as a corporate sale, merger or other combination
  • Collaborated extensively with CFO and engineering staff to create a net asset value model that reflected the company’s development schedule, capital costs, type curve analysis, midstream and operating assumptions
  • Prepared accretion-dilution analyses of merger scenarios for buyer-tailored transaction structures
  • Led coordination of detailed due diligence between client, buyer and its financial and legal advisors

Buy-side advisor to multi-billion dollar private equity firm in its evaluation of Haynesville gas assets 

  • Engaged by the firm to conduct extensive valuation analysis and due diligence to help inform a potential bid

  • Developed net asset value model of the Haynesville gas assets which included estimates of gathering and marketing contract liabilities sensitized over a variety of different production and contract renegotiation scenarios 

  • Proposed optimal bid sizes and structures based on modeled scenarios and potential synergies with existing firm-owned Haynesville gas assets 

University of Texas Undergraduate Computational Finance Group
Austin, TX
Volunteer Director
Spring 2014 - Spring 2017

  • Analyzed equity and derivative positions using fundamental and computational methods for a student-run fund
  • Presented over 10 different investment strategies and pitches as potential positions in the portfolio
  • Summarized market activity and analyzed key events in weekly reports sent to members and alumni

Pitched potential pairs trade of two diversified mining companies based on NAV modeling and quantitative analysis

  • Recommended a pairs trade based on the relative betas of the two companies to the price of iron ore
  • Built a NAV model of the focus company and conducted sensitivity analysis against changes in oil and iron price
  • Analyzed the effect of funds flow from emerging market ETFs on the market valuation of the mining companies

Presented other quantitative projects and investment strategies to the group utilizing derivatives

  • Built options pricing model in R using monte carlo simulations of historical returns to estimate option payout
  • Developed an algorithm to trade on contract rollover in volatility-tracking ETFs based on roll yield of VIX futures

Octavia Investments
Austin, TX
Hedge Fund Analyst Intern
Spring 2015 - Spring 2016

  • Analyzed potential investment opportunities for a long/short hedge fund with over $15 million in assets under management
  • Conducted detailed valuation of a $250B retailer to understand the impact of new segments to its intrinsic value; including a DCF valuation with forecasting models for each of the company's segments and sum of the parts multiples analysis to isolate the value of its growing e-commerce segment
  • Developed NAV models for 14 North American exploration and production companies; incorporating basin-specific well EURs, drilling costs, completion costs and spacing