PROFESSIONAL RESUME

Gustavo José Montenegro Castillo

Data Engineer/Big Data/ Business Analytics/Geostatistics/ Geophysicist /Machine Learning Experience

Summary:

* **** ** **** ********/Big Data & Business Analytics, working with data preparation (using Linux commands, SqLite, Python), Statistical analysis (using R: Glms, Logistic regression, Arima, lasso, Ridge), Machine Learning (using Python: sciKit-learn, Theano, Keras) as linear and Multi regression, K-nn, Decision Tree, K-means, random forest, SVM, Naives Bayes. Neural Networks using Octave, Theano, Keras. Doing Text Mining and Natural Language Processing using Python NLTK. Performing Business Intelligence using Pentaho. Big data using Hadoop (Hive, hdfs) AWS (sqs, cli, streaming, Ec2), Spark

(Sql, Streaming, SparkML). NoSql (MongoDb, Neo4j). Scala and scripting with Bash. Agil / Scrum. DataBricks. Gephi. IoT (Leshan). Location Analytics using R. ElasticSearch. 2 years working with SQL, linux command, awk, scripting in Bash doing the maintenance for a exploration and production database in the oil industry. 25 years of experience in the oil industry working as Geostatistics, Geomodeller, Geophysicist, building Geocellular models and making seismic interpretation supported by Machine learning algorithms, using Linear and multiple regressions, Neural Networks, K-means, Geostatistics analysis, Optimization and Montecarlo Simulation to support new well location in the oil industry. Programing in C++ and java, I have designed 2 Online Course for 5 days to teach: Introduction to Machine Learning for hydrocarbons using Octave and Applied Geostatistics for hydrocarbons. (www.IngeoExpert.com) Giving at least 20 Geostatistics & Geomodelling training course for national and international clients Key Qualifications:

Big Data & Business Analytics

SqLite, GitHub, Gephi

Machine Learning (Neural networks, K means, Logistic regression, gradient descent) Supervised Classification (K-nn, decision tree, random forest, SVM, Naives Bayes) Unsupervised classification (PCA, K-means)

Geostatistics

Statistical Analysis with R (Linear regression, Arima models, multiple regressions, Glms, Confusion matrix) Python (pandas, json, sciKit-learn, Theano, NLTK, Keras) Linux(Ubuntu), awk, grep, sed, bash, vi.

Big data using AWS (sqs, cli, streaming, Ec2), Hadoop (Hive, hdfs) Spark (Sql, Streaming) Business Intelligence using Pentaho BAS

Matlab, Octave, C++, java

NoSql( Cassandra, MongoDb, Neo4j)

Doing pre-sales & post-sales of software giving national & international presentations 2181 Dunlap ST

Charleston, SC, 29406. USA

Email = adbxwj@r.postjobfree.com

Phone: +1-843-***-****

Nationality: Venezuelan

Status: Work Permit: OK

SSN: OK.

Language: Spanish / English (IETLS: 5.0)

Background: Data Engineer, Geostatistics, Big Data & Business Analytics, Machine Learning, Geophysics, Geomodelling

Education: Msc. Big Data & Business Analytics, IMF Business School, Spain (2019) Machine Learning Certification, COURSERA, (Stanford University) (2017) Msc. Geophysics (Half career) Venezuela Central University. (2016) Systems Engineer. Open National University, Caracas – Venezuela. (2000) Professional History:

2017 up to date: Independent Consultant (Geophysicist & Geostatistics & Machine Learning) Making Geostatistics model and doing seismic interpretation on Petrel to characterize hydrocarbons reservoir using machine-learning algorithms like multi regression, k-means, fisher discriminant, Monte Carlo simulation, logistic regression and neural networks to support the new well locations. 2008 to 2016: Geophysicist/Geomodeller/Geostatistics/Machine Learning Gazprom Latin America Performing Seismic interpretation and building the static models on Petrel for new business for national and international client, supporting those interpretation with Geostatistics, Linear and multiple Regression, Neural Networks, K-Means algorithm, logistic regression using Matlab. 1998 to 2008: Geophysicist & Geomodeller. Champion Leader G&G for Venezuela and Trinidad Schlumberger SIS

Consultant in Geophysics, Geology, GeoModeling 3D and Geostatistics for national and international clients in Colombia, Argentina, Trinidad & Tobago, Ecuador and giving training for PDVSA and International clients (Repsol, Shell, Ypergas, BG, Hocol, Petrobras, ENI, CNPC) in the training center of Schlumberger Venezuela on the software: PETREL & Geoframe supporting those activities with Geostatistics, and machine learning algorithms like Linear and multiple Regression, logistic regression, Neural Networks, K-Means algorithm. Doing Pre-sales & Post Sales for the software Petrel & Geoframe. Programing plugins for Petrel application on Visual Studio (C++). 1997 (9 months): Application Support Gesca – CogniSeisC.A Application support in Seismic Interpretation (VoxelGeo). 1996 (6 months): Seismic Acquisition 3D Suelopetrol C.A Working in the assistance of the planning for the Acquisition seismic 3D. 1994 to 1996. Data Analyst Keycad c.a – Lagoven S.A Working with SqlPlus and Pl/Sql to support the daily activities in the maintenance of the exploration and production database for Lagoven (PDVSA)

Some programs developed as Data Engineer/Big Data/Business Analytics Using Linux commands and Python to manipulate and evaluate Tweets data Making a logistic regression models to predict bank credit approval in R Making a multi regression model to predict gasoline consume using Python (scikit-learn) Making a Theano model to minimize w0 and w1 in a logarithmic function. Making a K-means model in Python (SciKit-Learn) to classify the crimes in a country. Making a tagger to recognize request of food using NLTK in Python with a Spanish corpus Making a NaivesBayes classifier to recognize kind of food requested for a client Making Business Intelligence using Pentaho BAS doing analysis on statistical values Processing data with AWS and using Hadoop (Hive, hdfs), Spark( Sql, Sreaming) Using Gephi to process twitters (communities classifications, reports, analysis) Using Sql on PySpark/DataBricks to process Big Data predicting features with Decision Tree Model. Some programs developed for Machine Learning

Using gradient descent algorithm in Linear Regression to find the best time – depth relationship in Octave Using gradient descent algorithm on Logistic Regression to classify seismic attributes in Octave Using neural networks to perform predictions in a Psychology issue with Python/Keras Using K-Means algorithm to classify seismic attributes in Octave Using MonteCarlo simulation to perform seismic inversion in Matlab Developing models to predict sports winner (Basquetball and Baseball) with Octave Developing an ARIMA model to predict the new registered student in an open university. Developing for the Master thesis a model to predict basketball game winner using neural network with

(Python/Keras)

Certifications, Courses:

SqlPlus Oracle Venezuela

Pl/Sql Oracle Venezuela

Publications:

Published Book: Basic principles to build geocellular models, June 2013, sold on Amazon. Paper: M.Nieto, G.Montenegro (Baker Hughes Ecuador), R. Diaz (Petroamazonas)., U Sandstone Geocellular Model, Culebra Yulebra Field., Heavy Oil Latin America Conference, Venezuela 2014.