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Sr. Data Scientist (sme) Resume

Austin, TX


  • An expert in utilizing mathematical modeling for business problems by research with practical attitudes toward problem - solving.
  • Twenty years of experience as a researcher in academia and four years of industry experience as a subject matter expert for finding solutions for new analytical technologies, applying machine learning in production and big data environments in ambiguous situations.
  • Exceptional business problem solvers and a deep thinker with cleverness in choosing the right strategies for high-impact delivery on time.
  • An interdisciplinary researcher with strong analytical and numerical skill sets.
  • Goal oriented and believes in effective communication to achieve common goals.
  • Resourceful and a master at keeping up with latest technologies and turn them into solutions.
  • An established data scientist practicing machine learning in the oil industry, big data attribute recognition in the IT industry, and a well-known Confidential information scientist for building Confidential computers.
  • Proven collaborative ability to work with analysts, platform engineers, and scientists with top performance.
  • A unique trait of being intuitive in grasping the big picture of problems and methodological in solution finding.
  • Expert in formulating business problems in terms of mathematical formulation and finding solutions
  • Data analytics in high-tech. industry and academics by data inspired machining learning (from top to bottom) or physics inspired modeling (from bottom to top).
  • Ability to implement and elevate machine learning algorithms from scratch when needed
  • Deep understanding and working experience for machine learning algorithms including generalized linear regression model, PCA, SVM, random forest with boosting, cluster analysis, anomaly detection, the neural network with applications to supervised and unsupervised learning problems
  • Expert in applying technologies to bridge the gap between analytical side with engineering side of business
  • Productive mentoring and leadership ability toward subordinates
  • Expert in prototyping and modeling business problems quantitatively so that it can be generalized in practice
  • Excellent prototyping skills and production-grade programming with Python, R, Scala, Matlab, Fortran, and C++.
  • Experts in utilizing machine learning platforms for big data in clouds and mainframe computers such as Spark, H2o, Qubole, and TensorFlow
  • Software engineering knowledge in bridging gaps toward goals by using the latest technologies
  • Big data ecosystems with Hadoop, Hive, H2o, and Spark with R/Python APIs
  • Real-time data and batch processing and prediction with Kafka and Spark
  • Distributed computation programming in Apache Spark and MPI
  • Excellence on keeping up latest development in theoretical science and applying it in terms of numerical solutions at scale
  • Strong hands-on knowledge in software development and distributed computing environment
  • Technical expertise in machine learning algorithms, tools, and platforms for model and deployment
  • Good history of publications in well-respected journals, conference proceedings and a good track record of building significant data science capabilities in the industry
  • Optimization algorithms including gradient-descend, stochastic gradient-descend, conjugate-gradient, annealing algorithms, the imaginary time evolution algorithms
  • Experts in open communication and mentoring
  • Excellent presentation and communication skills - particularly strong in visualizing and presenting complex data and analytical findings to non-technical audiences. Ability to decipher hidden user needs
  • Excellent understanding of experimental design, A/B and multivariate testing
  • NOSQL/SQL database


Sr. Data Scientist (SME)

Confidential, Austin, TX


  • Created a solution to enable spark-based machine learning models to do real time scoring in AWS with the latency of millisecond per record
  • Created machine learning models for classifying different types of rmation identification (PII) and attribute recognition
  • Proof of concepts for machine learning model building and finding user cases for the business
  • Consultant role for big data tools and machine learning based AI services
  • SME for machine learning algorithms and platforms

Certified Data Scientist

Confidential, New York, NY


  • Created interactive API for comparing the regional living cost and data scientist compensation
  • With visualization by programming in R Shiny
  • Scrapping MLB baseball pitcher statistics by Python Selenium for the prediction of winning performance with a linear regression model
  • Answered the correlation between stocks from semiconductor manufacturers, financial industries, and oil Giants by quantitative time series data analysis
  • Invented a new stacking model for network intrusion detection (or fraud detection) with logistic regression, principal component classifier, Naïve Bayes model, and tree-based models in R and Python
  • Higgs-boson signal detection by artificial neural network algorithm.

Acoustic Research Scientist (SME)

Confidential, Houston, TX


  • Developed a nonlinear regression model in C++ to invert rock formation properties(stiffness) from full acoustic waveforms by gradient-descend algorithms (logging tool effects are included)
  • Produced advanced multiple sensor signal processing in most advanced borehole acoustic applications in the energy industry

Postdoctoral Scientist

Confidential, Los Alamos, NM


  • Parallel Programming with MPI in Fortran and model building in supercomputers to understand why two chemically similar Pu compounds are so different in magnetically and electronically, resolving of the long-term puzzle
  • Predicted the possible existence of topological states in Iron-based superconductors by nonlinear optimization algorithms with boosting

Postdoctoral Scientist

Confidential, Washington, DC


  • The lead Confidential theory researcher with top publications in Nature, Science, and Nature Communication
  • Develop a coherent theoretical description of ultracold ion Confidential computers
  • Developed a forecasting model for the states of a Confidential annealing computer based on Confidential annealing algorithms
  • Developed a new theoretical model for the dynamics of a Confidential computer predicting novel spin-liquids phenomena confirmed by experiments

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