Data science experience
Nikolai Shokhirev, Ph.D.
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Nikolai Shokhirev
I am a Physicist by training and hold a Ph.D. degree in Physics and Mathematics (Theoretical Physics).
I am not a conventional Data scientist, but Data science always was a significant part of my professional
activity from research to engineering to retail to finances.
Data science definition
Data Science is an interdisciplinary field about processes and systems to extract knowledge
or insights from large volumes of data.
Data science main components

Scientific Method  Reasoning Principles (inductive, and deductive), Empirical Evidence, Hypothesis Testing

Data Engineering involves acquiring, ingesting, transforming, storing, and retrieving data, metadata

Mathematics, Statistics, Applied math, Probability theory, Machine learning

Advanced computing

Domain Expertise
To some extent I have experience in all the above listed areas:
Scientific method

Quantum mechanics, Statistical physics  probabilistic approach, probability models.

Statistical physics, Kinetics: Detailed balance, Metropolis algorithm  a.k.a. Markov chain Monte Carlo.

Mathematics, Calculus, Ordinary and partial differential equations, Intergral equations,
Green's function, Probability theory, Statistics.

Indirect measurement and remote sensing  Analysis of accuracy, resolution, domain of reliable reconstruction using SVD.

Stochastic processes, Stochastic differencial equations.
Data engineering

Data acquisition, Raw data collection, Financial data management on GB and TB scale.

Data format (XML, JSON, YAML, CSV, etc.), Data storage/retrieval (Relational DB, SQL, NoSQL MongoDB, Neo4j), Metadata.

Data cleanup (Missing data, interpolation, noise filtering)  e.g. correlation matrix must positive definite.

Data transformation (scaling, normalization, aggregation).

Data integration (Combining data from various sources).

Data validation (Error checking, anomaly detection).

Data presentation, Dimensionality reduction, Data visualization (historic data exploration tools, correlation visualization).
Scientific, engineering and financial data analysis and processing

Probabilistic models (Stochastic models in Statistical Physics, Kinetics and Spectroscopy).

Inference from data, Knowledge extraction, Statistical learning, Statistical inference (Statistical analysis of Protein data, Correlations, PCA).

Model development  (Dynamic, Quantum and Stochastic modeling  ODE, PDE, SDE).

Prediction, Classification (which is prediction as well), Decision support, Recommendation systems.

Pattern recognition/ Identification (Spectroscopy, Finances).

Forecasting, Predictive analytics, Extrapolation, Regime change detection.

Signal processing  1D and multidimensional spectroscopy.

Time series analysis: Fourier and Wavelet analysis, Regressions, Running averages and other statistics, Autoregressive models.

Gaussian process regression (Bayesian "nonparametric" nonlinear regression).
Advanced computing

Over 10 years of software development (Full software development life cycle, SDLC tools and methodologies), Scientific and Technical programming.

Various languages (OO Python, C#, C++, Delphi, FORTRAN) under Windows and UNIX/Linux.

Relational (MS SQL Server, Oracle, MySQL, SQLite, Interbase, DB2, Access, PostgreSQL), NoSQL (KDB, RexDB), Documentbased (MongoDB),
Graph (Neo4j) databases.

Statistical, Machine learning and Data processing libraries (IPython, Jupyter, Pandas, NumPy/SciPy, MatPlotLib, Scikitlearn).

Analytical tools (R, Matlab, Mathematica).

Numerical methods and algorithms, Finite element methods, Optimization, QuasiNewton method, Evolutionary algorithms,
Stochastic optimization, Monte Carlo.
Domain expertise

Financial instrument and risk valuation.

Market statistics and analytics.

Financial and retail data management.

Scientific and financial analytics.

Quantum mechanics, Magnetic spectroscopy (MNR, EPR), Kinetics, Chembioinformatics.

Indirect measurements and remote sensing in science and engineering.
See more details in my online Detailed resume ,
Professional highlights and Ppublications.
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© Nikolai Shokhirev, 20122017
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