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Data Scientist Resume

OBJECTIVE:

Data Scientist, Machine Learning, AI development. Has built several world class Artificial Intelligence Machine Learning products for diverse industries

SUMMARY:

  • Machine Learning for Predictive Analytic and Artificial Intelligence
  • Natural Language Processing NLP
  • Deep Neural Networks
  • Statistical Inference
  • Analytical and Numerical Statistical Analysis
  • Stochastic Data Computer Simulation
  • Neural Science
  • Data Visualization
  • Algorithms Developing and Coding by Myself
  • Software skills such as Python, R, Matlab, SQL, NoSQL and C++
  • Real - World Data & Industry experience
  • Experience in many programming languages
  • Customizing new approaches from Data Science research
  • Taught in Universities and Industry
  • Reviewed Machine Learning models and code developed by others

CAREER HISTORY:

Data Scientist

Confidential

Responsibilities:

  • Artificial Intelligence Machine Learning: Recommendation systems, Classification, Natural Language Processing (NLP), NoSQL, Python coding by myself

Data Scientist

Confidential

Responsibilities:

  • Predictive Modeling Machine Learning and Deep Neural Networks for Natural Language Processing and Sport Predictive Analytics (coding in Python and R). Random Forest and GBM regression.
  • Twitter Sentiment Analysis and Language Identification for Social Media Predictive Modeling Analytics, Theano, Keras.

Data Scientist

Confidential

Responsibilities:

  • Developed Predictive Modeling for Real Time Streaming Data Classification Algorithms for Revolutionary monitoring of different stages of sleep and Surgical Anesthesia using Auditory Brain Response (Auditory stimulation and Confidential / Confidential (event-related Confidential ) signal processing)
  • Along with other neurological data algorithms, worked with ABR (auditory brainstem response) and ASSR (auditory steady state response) detection
  • Machine learning Predictive Modeling algorithms development to classify Confidential data mixed with brain auditory evoked response. Combining several supervised machine-learning methods. Data Visualisation, Acquisition, Cleaning and Processing implemented by Python, Matlab and C++.
  • Brain auditory response extraction from Confidential by data de-noising and processing. Statistical inference about how brain auditory responses present in Confidential .
  • Predictive Modeling Statistical inference (estimation/detection) about buried-in noise physiological signals in non-stationary additive noise - Physiological Radar Data Statistical Inference.

Data Science Consultant

Confidential

Responsibilities:

  • Performed fast customizing of my Dynamic Programming model algorithms for wireless telecommunication
  • Complicated Simulation of Time Series by Matlab and C
  • Performed investigation of Noise Statistical Characteristics and Statistical Performance of Streaming Data Processing

Data Scientist, Big Data Research

Confidential

Responsibilities:

  • Revolutionary Big Data Streams Optical processing, theoretical analysis, simulation, and experimental set ups.
  • Numerical simulation solutions of the partial non-linear differential equation using the Split Step Fourier Method (Matlab, C). Working with all main C++ compilers: UNIX, Microsoft, Intel, Texas Instruments, and Borland.
  • Real-Time control engineering. Development of Real-Time Matalb data acquisition code and algorithm design and implementation. Image and graphic visualisation of random walk time series by Matlab. Statistical inference in real-time and offline mode.
  • Wavelets data processing: algorithms development, Matlab simulation and visualization.
  • Matlab-coded graphic user interface: parameters input, results output, behavioral descriptive cartoons.
  • Mathematical theoretical and numerical analysis of time series non-linear distortions
  • I solved the famous problem of multi sensor fusion for time and spatial encoded data for real non-Gaussian noise. I developed a theoretical foundation for how to use robust statistics theory to design statistical inference to solve this problem. I also developed a method for the theoretical probabilistic analysis of conventional methods and suggested new methods as well. Simulated stochastic behavior by Matlab.

Data Science Consultant

Confidential

Responsibilities:

  • Developing Predictive Modeling Analytics, Simulation and Analysis for signal propagation and processing for RF repeater - fast company eyes opening on what and how to develop. Coding in Matlab and C

Data Scientist

Confidential

Responsibilities:

  • Big Data Streams Time series Machine Learning Classification and design and simulation (Matlab, C, SPW) for Confidential Third Generation wireless internet and voice data - demonstrated best worldwide abilities to develop algorithms to implement most sophisticated statistical data processing and technical standards requirements: discreet and continuous stochastic processes and their generation, as well as transformation and statistical inference
  • Inspected/reviewed designers and programmers of Confidential .
  • Provided expert advice in developing and testing algorithms. Confidential and CDMA 2000 standards teaching and consulting for company staff

Data Scientist, Big Data Research

Confidential

Responsibilities:

  • Developed and simulated one of the earliest Big Data Sampling methods. Operation systems: UNIX and Windows. Computer languages: C and Matlab.
  • Development of a Predictive Modeling Machine Learning method for prediction and control of Supervised Random Walk in the context of internet traffic data packages routing. I developed a probabilistic approach for algorithms design and quantitative performance analysis. Simulations coded in C and Matlab.
  • Taught a course of “Statistical Data Processing for Analog and Digital Communication Systems”

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