Data Science and Analytics Resume

PROFESSIONAL SUMMARY:

SAS Data Analyst with 5+ years on the IT Industry and strong analytical skills.
Commercial experience in the implementation of business intelligence and decision engine systems, and credit risk data analytics in retail banking and financial services industries using SAS and SQL.
Hands on experience with statistical analysis, machine learning and big data analytics using R, Java, Hadoop/MapReduce.
5+ years as Data Analyst in Retail Banking/Financial Services/Credit Risk using SAS (Base, EG, Macros, SQL).
2+ years as Business Intelligence Analyst using SAS.
1+ year as Data Scientist: Predictive Modeling, Statistical Analysis, Machine Learning, Big Data (Hadoop/MapReduce, Mongo DB), R, SQL, Java.

TECHNICAL SKILLS:

SAS: SAS Base, Enterprise Guide, Data Integration(ETL), OLAP StudioMacros, XML Mapper

Machine Learning: Algorithms for classification, regression and clustering:K - Nearest Neighbors, Linear Regression, Logistic Regression, Decision Trees, Decision Stumps, Linear Discriminant Analysis, Quadratic Discriminant Analysis, Neural Networks, K-means clustering, Hierarchical Clustering, Markov ModelsOverfitting/Underfitting, Bias/Variance trade-off, Regularization, Validation set approach, Cross Validation, Bagging, Boosting, Model Accuracy/Prediction error, Principal Component Analysis.

Statistics: Continuous and Discrete Probability Distributions, Expectation/Variance and other moments, Independence, Hypothesis Testing, Non-parametric statistics.

Big Data: Hadoop, MapReduce, Java

Java: Functions, classes, input/output, text processing, regular expressions, arrays to represent and manipulate graphs, hashmaps.

Python: Lists, Dictionaries, Functions, Numpy

Programming Languages: R, SQL, SAS programming, Java, Python

Databases: PostgreSQL, MongoDB.

Operating Systems: Windows 8, Unix(Basic)

IDE: Eclipse

Other: Data Acquisition, Data Types, Data Processing, MS Office, Weka, Twitter API, Matlab

PROFESSIONAL EXPERIENCE:

Data Science and Analytics

Confidential

Responsibilities:

Implemented algorithms for regression, classification and clustering by coding my own programs using R, such as:
Designed and implemented an information system for a small chain of electronics stores. Using PostgreSQL, defined SQL and DDL scripts, created a sequence of statements to populate the database, and defined queries to obtain the information required.
Implemented Large Scale Data Storage and Processing projects: Data Acquisition using Twitter API, Data Storage and Processing, Simple Social Network Analytics, Twitter Sentiment Analysis with Java and MongoDB, Social Network Graph Analysis using SQL, and Big Data: Data Mining with Hadoop and Gephi and implemented MapReduce programs on HDFS using Enron dataset.
Implemented machine learning algorithms for smart meter data to predict gas consumption. Using Java, I wrote a MapReduce job to aggregate the big dataset as required, and executed it in Hadoop cluster. Then uploaded the output in R, and used Linear Regression and Decision Trees, and finally utilized more complex algorithms such as Neural Networks and Ensemble Methods to improve prediction performance.

Confidential

Responsibilities:

Performed data analytics to create rules and statistical models such as decision trees, logistic regression and k-means clustering to identify customers with higher risk and groups of customers with similar payment or usage behavior.
Supported the consultant TransUnion for the development and validation of new credit scoring models for the bank.
Developed, tested and implemented segmentation algorithms using SAS, to assign initial credit limits and risk based pricing strategies for the credit card portfolio.
Set up a process, coding in SAS, to extract, transform, load (ETL Processes) and integrate information from different sources for the Risk department.
Implemented and managed Capston Decision Accelerator, a FICO’s decision-making engine to assess credit card applications.
Collaborated with a multidisciplinary team with technical and non-technical backgrounds such as IT, Commercial, Credit and Product departments to design, develop and implement a workflow strategy for credit card origination.
Contributed to the implementation of the Credit Bureau services in the credit process through the integration of the two Credit Bureau services providers in Mexico.

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