Data Scientist Resume Washington DC - Hire IT People

SUMMARY:

AI Scientist, Data Scientist with Engineering and Computer Science background. Exploring the capabilities of modern artificial intelligence and deep neural network solutions to practical problems.
As a Data Scientist, experimenting and implementing data analysis methods with efficient tools to derive accurate outcomes from big data.
Experience in developing end - to-end ML pipelines and deployments. Provided computational collaboration to scientific research through molecular models, simulations and data analysis in academia.
Consulting experience with communication with clients, storytelling and creating production-development plans.
Strong analytical, technical, self-learning and problem-solving skills. Responsible team player. Moo Sul Kwan Taekwondo Brown Belt. Enjoys outdoors, painting, gardening and music.

TECHNICAL SKILLS:

DATA SCIENCE, AI & COMPUTATIONAL SKILLS: Deep Learning, Neural Networks, Big Data Analytics, Machine Learning for Computer Vision, Text and Voice Analysis, Natural Language Processing, Data Visualization, Graph Data Bases, Object - Oriented Programming, Web Scraping, Rest API, Data Mining & Wrangling, Statistical Analysis, Time series Analysis, Entity Resolution, Topic extraction, Distributed Computing, Sentiment Analysis, Classifications, Clustering, Decision tree learning, Regression, Random Forest, Gradient Boosting, Latent Dirichlet Allocation (LDA), Gibbs Sampling, Principle Component Analysis (PCA), Fast Fourier Transform (FFT), Robotic process automation (RPA), Vector Regression Models (VAR), Autoregressive Integrated Moving Average (ARIMA), ARIMA with Seasonal Correction (SARIMAX), Support Vector Machines (SVM), Bag of Word method, TF-IDF (Term Frequency- Inverse Document Frequency), Search Algorithms, Heuristic techniques, Operational Research, Optimization algorithms, linear programming, simulated annealing, Agile, Scrum, Kanban.
TOOLS: Python, R, TensorFlow, Keras Torch, Pytorch, OpenCV, ImageMagick, Docker, Flask, Hug Apps, swift, RStudio, Julia, Golang, Spark, Neo4j, Cypher, NLTK, CNN, RNN, LSTM, GANs, Autoencoders, ResNet, YOLO, dlib, One-shot learning, NVIDIA GPU-based Deep Learning, Git, pytest, unittest, Numpy, Scipy, Matplotlib, seaborn, plotly, Tableau, BeautifulSoup, Scikit-learn, XGBoost, Pandas, Spacy, Scrapy, Solr, Hue, Keras, Gephi Graphs, NetworkX, Theano, ggplot2, rvest, Shiny, D3, Elastic search, PostgreSQL, DBMS, R DBMS, mySQL, FORTRAN, MPI, HPC, C, C++, XML, HTML, CSS, JavaScript, MATLAB, AutoCAD, MS Office, MacOS, Linux, Unix, MS Windows, Jupyter Notebooks, JupyterHub, AWS platforms: AI/ML, EC2, S3, cloud 9, AWS API gateway, Dynamo DB, Athena, Lambda, Google AI, Azure.
CHEMICAL ENGINEERING SKILLS: Simulation Techniques, Molecular Dynamics, Monte Carlo simulations, Quantum Mechanical calculations, Density Functional Theory, Reaction Engineering, Fluid Mechanics, Thermodynamics, Statistical Mechanics, Transport Phenomena (air/gas/liquid), Catalysis, Polymer technology, Environmental Engineering, Material Science, Plant Safety and Risk Management, Process Design, Energy Systems, Unit Operations.

PROFESSIONAL EXPERIENCE:

Confidential, Washington DC

Data Scientist

Responsibilities:

Electrical Engineering, Energy Transmission, phasor measurement unit (PMU)
Synchrophasor data analysis, signal processing, forecasting, event detection & classification, anomaly detection, data quality analysis, supervised and unsupervised machine learning. Deep Learning for energy grid data: CNN, LSTM

TinmanKinetics, Littleton, CO

Senior AI Scientist

Responsibilities:

Image and video analysis, Voice recognition for different field of studies (terminology), Text analysis, Image aesthetics, Image personalization, Face Recognition, Text recognition, Classifications, Object Detection. CNN, RNN, LSTM, GAN, Autoencoders, Robotic process automation (RPA), Data mining and analyzing, AI app development. Prototype and Demo.

Confidential, Arlington, VA

Data Scientist

Responsibilities:

Data tree structures, Text Analysis, NLP, Interactive Data Visualizations, Graph Data Bases, Distributed Data Base Systems,
Topic modeling and identifying key-phrases in unstructured text data using NLTK and Gensim. Data extraction and collection, Data cleaning and ingestion, Risk Analysis.

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Data Scientist Resume

Washington, DC

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