MADHUKAR MANTRAVADI

AUSTIN, TEXAS 210-***-****

ac7z28@r.postjobfree.com http://madhukarmantravadi.net PROFILE

Data-focused engineer with a deep passion for pushing myself with new challenges and being outstanding at what I do. I have experience in Python, predictive analysis, SQL, Machine Learning, Deep Learning, and Data Modeling. My goal is to be the go-to person when a difficult problem arises. I utilize my breadth of knowledge to output efficient results in a timely manner, because computational time is money. SKILLS

Programming languages: Python (Pandas, Numpy, Scikit-Learn, Selenium, MatPlotlib, Seaborn, PlotLy), MATLAB, postgreSQL, Scala, Git, LabView, C++

Software knowledge: Tableau, Excel, PowerPoint, Word, SolidWorks/AutoCAD

Data science: Predictive/Statistical Analysis (SVM, Random Forest, KNN, Clustering, XGBoost), Unstructured and Structured Data, Exploratory Data Analysis, Deep Learning (Keras, Tensorflow), NLP (LDA, vectorizing, word2vec), APIs, Machine Learning, Big Data (Mapreduce, Spark, AWS), Jupyter Notebook EXPERIENCE

General Assembly, Music Genre Classifier Sept. ‘18 – Oct. ‘18

Processed and performed data exploration on the 300+ GB Million Song Dataset

Utilized LDA method to engineer features for all 200,000 songs with lyric information

Hosted my project on AWS and used multiprocessing to optimize

Used Logistic Regression, Random Forest, and Gradient Boosting to find the best model to classify song genre based on words used and engineered features

General Assembly, Chicago West Nile Predictive Analysis Aug. ’18 – Sept. ‘18

Cleaned and prepared a 10000+ point dataset from Kaggle with statistics about West Nile Virus in Chicago from 2007-2014

Constructed Random Forest, Logistic, and Support Vector Classifier models to predict when and where different mosquitos will test positive for West Nile virus

Utilized git for version control within the project with a small team of 4 Faurecia, Acoustic Engineer June ‘16 – Jan. ‘17

Undertook a sound quality project to help minimize misunderstandings with clients

Wrote MatLab code to analyze 100+ sound files for calibration using a binaural head

Collected a total 10,000+ points of subjective opinions on the sounds

Used ArtemiS and MATLAB to make a set of plots to map subjective keywords to objective metrics

Presented my results in front of how many? and helped the company's engineers better understand clients EDUCATION

GENERAL ASSEMBLY Certificate of Data Science

UNIVERSITY OF TEXAS, AUSTIN Bachelor of Science in Mechanical Engineering