Soccer Statistics
BILAL KHAN
10400 NE 2nd St, Bellevue WA 98004
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------------/in/bilalkhan86
bilalmkhan.github.io
Work authorization: US Permanent Resident
SKILLS
PROGRAMMING TOOLS: Python, Scikit-Learn, Pandas, NumPy, Matplotlib, Seaborn, NLTK, TensorFlow, Keras, SQL, Spark, MLlib, Hadoop, R, AWS.
MACHINE LEARNING: Supervised and unsupervised learning including Linear Regression, Logistic Regression, Decision Trees, Ensemble Methods (Random Forests, XGboost), SVM, Naive Bayes, K-Nearest Neighbors (KNN), K-means Clustering, Hierarchical Clustering, PCA, Natural Language Processing (NLP), Deep Learning (MLPs, CNNs, RNNs, LSTMs).
STATISTICS: Design of experiments, hypothesis testing, A/B testing, multiple regression analysis, analysis of variance (ANOVA), time series, bootstrapping.
RELEVANT EXPERIENCE
Data Scientist (Contract), Microsoft, Bellevue WA, Oct 2018 – Mar 2019.
- Collaborated with the Microsoft’s ‘Outings’ travel app team daily to constantly improve the product and analyzed the app’s data to clean it and to yield insights.
- Trained text classification models with an accuracy above 97 percent using cutting-edge deep learning and natural language processing tools (e.g., Attention-based RNNs, ELMO).
- Used text classification models to find percentage of travel URLs in the database relevant to the ‘Outings’ app broken down by different domain names to identify good data sources.
- Employed multi-class text classification models to calculate the percentage of different entity categories (parks, beaches, museums, etc.) represented in the Outings database.
- Constructed text similarity measures to identify and remove duplicate URL entries in the database. Calculated the percentage of duplicate entries broken down by domain.
- Carried out queries for unstructured data from Microsoft’s Cosmos DB using the Scope query language.
EDUCATION
- PhD in Economics, Northern Illinois University, August 2014
(Dissertation: Optimal Duration in Online Auctions with Stochastic Bidder Arrival)
- BS Economics and Mathematics, Graduation with Merit, LUMS, June 2008
OTHER EXPERIENCE
- Math Instructor, Probability and Game Theory, Johns Hopkins Center for Talented Youth Summer Programs, (June to August) 2012 – 2018
- Assistant Professor, Department of Economics, LUMS, 2014 – 2017
BILAL KHAN
10400 NE 2nd St, Bellevue WA 98004
------------
------------
------------/in/bilalkhan86
bilalmkhan.github.io
Work authorization: US Permanent Resident
SKILLS
PROGRAMMING TOOLS: Python, Scikit-Learn, Pandas, NumPy, Matplotlib, Seaborn, NLTK, TensorFlow, Keras, SQL, Spark, MLlib, Hadoop, R, AWS.
MACHINE LEARNING: Supervised and unsupervised learning including Linear Regression, Logistic Regression, Decision Trees, Ensemble Methods (Random Forests, XGboost), SVM, Naive Bayes, K-Nearest Neighbors (KNN), K-means Clustering, Hierarchical Clustering, PCA, Natural Language Processing (NLP), Deep Learning (MLPs, CNNs, RNNs, LSTMs).
STATISTICS: Design of experiments, hypothesis testing, A/B testing, multiple regression analysis, analysis of variance (ANOVA), time series, bootstrapping.
RELEVANT EXPERIENCE
Data Scientist (Contract), Microsoft, Bellevue WA, Oct 2018 – Mar 2019.
- Collaborated with the Microsoft’s ‘Outings’ travel app team daily to constantly improve the product and analyzed the app’s data to clean it and to yield insights.
- Trained text classification models with an accuracy above 97 percent using cutting-edge deep learning and natural language processing tools (e.g., Attention-based RNNs, ELMO).
- Used text classification models to find percentage of travel URLs in the database relevant to the ‘Outings’ app broken down by different domain names to identify good data sources.
- Employed multi-class text classification models to calculate the percentage of different entity categories (parks, beaches, museums, etc.) represented in the Outings database.
- Constructed text similarity measures to identify and remove duplicate URL entries in the database. Calculated the percentage of duplicate entries broken down by domain.
- Carried out queries for unstructured data from Microsoft’s Cosmos DB using the Scope query language.
EDUCATION
- PhD in Economics, Northern Illinois University, August 2014
(Dissertation: Optimal Duration in Online Auctions with Stochastic Bidder Arrival)
- BS Economics and Mathematics, Graduation with Merit, LUMS, June 2008
OTHER EXPERIENCE
- Math Instructor, Probability and Game Theory, Johns Hopkins Center for Talented Youth Summer Programs, (June to August) 2012 – 2018
- Assistant Professor, Department of Economics, LUMS, 2014 – 2017