Data Scientist / Machine Learning Engineer Resume Dallas, TX - Hire IT People

SUMMARY

Data Scientist with 7 years of experience executing data - driven solutions with adept knowledge on Data Analytics , Text Mining , Machine Learning ( ML ), Predictive Modelling , and Natural Language Processing ( NLP )
Proficient in Deep learning and Artificial Neural Networks for NLP such as Convolution Neural Networks, Recursive Neural Networks and Recurrent Neural Networks
Highly competent at wide varieties of Data Science programming languages and Big Data tools such as Python, R, SQL, Tableau, Sci-kit Learn, Hadoop, Spark, and Hive
Built models with TensorFlow and acquainted with top-level frameworks such as Keras, Theano and PyTorch
Processed large data sets in Python with libraries such as NumPy, SciPy and Pandas for data analysis and numerical computations to ready the data for ML algorithms
Developed predictive models using Random Forest, Boosted Trees, Naïve Bayes, SVM, Logistic Regression, and Neural Networks
Experience with relational and non-relational databases such as MySQL, SQLite, MongoDB, and Cassandra. Implemented POC using Spark SQL and Mlib libraries
Concrete mathematical background in Statistics , Probability , Differentiation and Integration, and Linear Algebra and Geometry
Acquainted with all aspects of Software Development Lifecycle (SDLC) from requirement analysis, Design, Building Coding, Testing, Deployment, and Maintenance in both Agile and Waterfall methodologies
Strong technical expertise at creating advanced machine learning algorithms , validation techniques , predictive data modeling , data mining algorithms , topic modeling , and sentiment analysis on the text data to provide new dimensions to the conventional thoughts on businesses
Extremely organized with demonstrated skills to perform several tasks and assignments simultaneously within the scheduled time
Interpreted and communicated the use cases , patterns , results , validity , and metrics to other teams and management in a visual and plausible way

TECHNICAL SKILLS

LANGUAGES: Python | R

DATABASE: SQL | NoSQL | Microsoft Access | Oracle | Teradata

CLOUD SERVICES: Azure

METHODOLOGIES: Agile | Waterfall

PROFESSIONAL EXPERIENCE

Confidential, Dallas, TX

Data Scientist / Machine Learning Engineer

Responsibilities:

Built advanced Machine Learning classification models like XG Boost , KNN , SVM Regression and clustering algorithms Hierarchical Clustering and DBSCAN
Performed NLP by using techniques like Word2Vec, FastText, Bag of Words, tf-idf, Doc2Vec
Performed data analysis by using Hive to retrieve the data from Hadoop cluster, SQL to retrieve data from Oracle database
Handled importing data from various data sources, performed transformations using Hive, Map Reduce, and load data into HDFS
Created distributed environment of TensorFlow across multiple devices (CPU’s and GPU’s) and run them in parallel
Created various types of data visualizations using Tableau and other libraries like Matplotlib, Seaborn, ggplot2
Collaborated with internal business partners to identify needs, recommended improvements

Confidential, Atlanta, GA

Data Scientist

Responsibilities:

Performed Sentimental analysis in NLP on the email feedback of the customers to determine the tone behind the series of words by Neural Networks techniques like Long-Short Term Memory (LSTM) cells in Recurrent Neural Networks (RNN)
Deployed Keras and TensorFlow for NLP implementation and trained using cyclic learning rate schedule
Used Long-Short Term Memory (LSTM) for analyzing time series data in PyTorch
Utilized t-Stochastics Neighborhood Embedding (t-SNE) and Principal Component Analysis ( PCA ) and to deal with curse of dimensionality
Created Neo4j graph visualizations of data flow from source to product and performed data lineage searches
Proficient at statistical metrics like F-Score , AUC/ROC , Confusion Matrix and RMSE to evaluate different model performance
Generated ETL mappings, sessions and workflows based on business user requirements to stack data from source files, RDBMS tables to target tables
Extensively used HiveQL and Spark SQL query to extract the meaningful data and administered to external Hive Table
Implemented CRUD functionalities of the API to handle query requests from Neo4j database
Performed data visualization using various libraries and designed dashboards with Tableau , generated complex reports, including charts, summaries, and graphs to interpret the findings to the team and stakeholders

Confidential

Sr. Data Analyst

Responsibilities:

Developed a Churn model for the marketing team to reduce the retention rate of customers
Analyzed very large data sets to develop insights that increase traffic monetization and merchandise sales without compromising shopper experience
Built a Proof of Concept (POC) by researching the user behavior and historical trends and developed a fraud detection model strategy using Random Forests and Decision Trees
Experimented with multiple classification algorithms, such as Logistic Regression, Support Vector Machine ( SVM ), Random Forest, Ada boost and Gradient boosting using Python, Scikit-Learn and evaluated the performance on customer discount optimization
Analyzed data to identify glitches and cleaning it to reduce the distortions
Applied multiple Machine Learning ( ML ) and Data Mining techniques to improve the quality of product ads and personalized recommendations
Developed NLP with Deep Learning algorithms for analyzing text improving over their existing dictionary-based approaches
Addressed overfitting by implementing regularization methods like L1 and L2 in algorithms
Collaborated in building of high-performance low latency system to manage high velocity data streams
Employed statistical tests such as hypothesis testing, t-test, confidence intervals, error measurements
Performed various data manipulation techniques in statistical analysis like missing data imputation, indexing, merging, and sampling
Performed Exploratory Data Analysis ( EDA ) to maximize insight into the dataset, detect the outliers and extract important variables numerically and graphically
Worked with Hadoop Ecosystem covering HDFS , HBase , YARN and MapReduce
Developed Hive UDF's to bring all the customers emails into a structured format
Created different charts such as Heatmaps, Bar charts, Line charts
Worked in creating different visualizations in Tableau using Bar charts, Line charts, Pie charts, Maps, Scatter Plot charts, and Table reports

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Data Scientist / Machine Learning Engineer Resume

Dallas, TX

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