
Years Experience
Clients Helped
Completed Projects
Areas of Expertise
Areas of Expertice
Software Development
Writing lowlevel and highlevel applications. Using and managing software. Software Automation and software architecture documentation.
Software
Soft Skills:
Advise you how to use software tools.
Advise you what software tools to use and buy.
Handle communication between software tools.
Web development:
Angular
React 4+
jQuery
Vue.js
Nest.js
Node.js
ASP.NET
App development:
Android Studio
Xamarin
Ionic
Cordova
Electron
Node.js
Programming Languages:
JavaScript / Typescript
C / C++
C#
Java
R
F#
Python
PHP
MATLAB
Automation
Identify opportunities for automation within software processes.
Design and execute QA tests using scripts that automatically test functionality.
Run tests for databases, systems, networks, applications, hardware and software.
Identify bugs and quality issues in development, service or business processes.
Install applications and databases relevant to automation.
Collaborate with other business units to understand how automation can improve workflow.
Gather requirements from clients, customers or end-users to develop the best automation solutions.
Creating shareable and reusable virtual development environments in tools like Docker.
Continuous integration with tools like TravisCI.
Automating testing and deployment of code with tools like Jenkins CI.
Algorithmic Trading
Writing low latency code in C++17/20. Template meta programming. Using and understanding behavior of different compilers. Working with MetaTrader 5 brokers (ex Pepperstone) with MQL5
Algorithmic Trading
Please contact me for a more detailed description.
Embedded Engineering
Designing simple PCB’s and FGPA’s. Working with different embedded systems. Lowlevel code optimization using assembler instruction sets. Signal and radio processing.
Hardware
Design PCB’s and electrical circuits.
Work with analogue and digital (SDR) RF components.
Signal processing using DSP’s
Using FPGA’s to design simple logic.
Advise you what hardware components to buy.
Handle communication between hardware components.
Work with a wide range of different SOC’s and Embedded Systems.
Code optimization using different Assembler Instruction Sets.
Documenting hardware systems in SysML and according to ISO standards.
Data Science
Analyzing small or large amounts of data and discovering new insights and strategies. Making future predictions using time series analysis on existing data. Training and creating (deep) neural networks that can detect implementation specific patterns.
Data Analytics
Skills:
Preparing and Analyzing data with tools like NumPy and Pandas.
Working with unstructured, structured and streaming data.
Tuning hyperparameters of models to achieve higher score during evaluation process.
Dimensionality reductions of feature vectors and finding feature set using clustering methods like Mini Batch and Mean Shift.
Describing Qualitative and Quantitative Data.
Numerical Measures of Central Tendency and Variability.
Detecting outliers with Box Plots and Z-scores.
Bivariate Relationships.
Events, Sample Spaces and Conditional Probability.
Binomial Random Variables, Binominal Probabilities Normality, Sampling Distributions.
Inferential Statistics and Hypothesis Testing (ex. Population variance, median, etc.).
Nonparametric Test on two or more populations.
Sample size estimation and optimization.
Using Probabilistic Models and machine learning models
Models:
K-Means
KNN Clustering
Suport Vector Machines
Decision Trees
Linear/Logistic Regression
Time Series
Autoregression (AR)
Moving Average (MA)
Autoregressive Moving Average (ARMA)
Autoregressive Integrated Moving Average (ARIMA)
Seasonal Autoregressive Integrated Moving-Average (SARIMA)
Seasonal Autoregressive Integrated Moving-Average with Exogenous Regressors (SARIMAX)
XGBoost
Long short-term memory (LSTM)
QLearning
Supervised Learning
Transfer Learning
Deep Learning
Tools:
Tableau
SAS (Basic and Advanced)
Power BI (+ DAX)
Google Data Studio
Pandas
Matplotlib
Seaborn
Google Charts
Chart.js
Computing
Designing, wiring and testing computer clusters. Multi-process programming with tools like OpenMP. Writing and optimizing algorithms on the CPU and GPU.
Computing
Skills:
Using high performance computing frameworks to optimize algorithms in parallel applications in Python and C/C++.
Design simple or complex computer clusters and run calculations on them.
Mathematical fields:
Linear Algebra
Computational Number Theory
Emurative Combinatorics
Topological Combinatorics
Partition Theory
Graph Theory
Statistics
Cryptography
Complex Numbers
Tools:
CUDA
OpenMP
OpenCL
Computer Graphics
Creating 3D simulations in OpenGL and DX11. C++ development in Unreal Engine 4+ and Unity. Computational physics simulations in OpenCL
Computer Graphics
Please contact me for a more detailed description.
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