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@almokgalaka

Remote worker with 30+ years of experience - Last seen 1 year ago

C++, Java, Python Software Developer with strong Front/Back-End Development in JavaScript, HTML and CSS, R and SQL/SQLite (PostgreSQL/MySQL or NoSQL, MongoDB and DynamoDB).

Mostly Interested in Python/C++ Quants Development (Software/Systems Optimization, Restful API and Quantization/Linear Approximation), Statistics and Machine Learning techniques for Deployment.

🛂 Nationality	🇿🇦 South Africa
🏡 Residency	🇿🇦 South Africa
📍 Location	🇿🇦 South Africa
Remote OK	rok.co/@almokgalaka
🔗 Website	sdfljasfjkhsdfajsf ⭐️ Upgrade to Premium to contact
GitHub	sdfljasfjkhsdfajsf ⭐️ Upgrade to Premium to contact
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LinkedIn	sdfljasfjkhsdfajsf ⭐️ Upgrade to Premium to contact
Nomads.com	sdfljasfjkhsdfajsf ⭐️ Upgrade to Premium to contact
Instagram	sdfljasfjkhsdfajsf ⭐️ Upgrade to Premium to contact
Skilled in	html css and js django flask fastapi and restful api
Fluent in	english
Preferred timezone	GMT-11/GMT-6
Preferred annual pay (min)	$185,000/year
Preferred hourly pay (min)	$80/hour
Last seen	1 year ago
Signed up	3 years ago
Badges	👨‍💻 Remote worker 🎨 Maker 🎖 Early adopter

Employment

2010 - Now: Data Specialist @ DPME

2007 - 2010: Data Quality Specialist @ SARS

1998 - 2003: Instructional Designer/IT Training Specialist @ Telkom State Enterprise

1996 - 2003: Tutor/Lecturer @ Unisa

Side Projects

2024 - 2025: Learning Hadoop, PySpark and PyTorch. Configuring and forking files to myGithub/alm2036

2023 - 2023: Developing large/high level Distributed systems (Introduction to Scala)

2023 - 2024: Machine Learning for Finance in Python: Data prep/cleaning Data, Data Analysis, Statistics and deploying Machine Learning algorithms (Linear models, Decision Trees, XGBoost, Random Forest, KNN/NN and Ensemble methods) in Finance (Calculating expected losses: PD* LGD*AED and predicted future stock prices by getting SMA/ewma accuracy scores).

2023 - Now: Using Python and Pandas for Data Engineering - Designing, developing and implementing data pipelines. Solving Life problems using AI & ML (e.g., A Candidate Model): Building Library for future/young Actuaries and Computer Scientists using Apparate and Geckodriver tools to extract file /or execute source file/my profile (else redo candidate model/profile with bash command) whereas on Github I configure files and or fork files. Writing proper scientific Python program names and applying Python Syntax rules.

2023 - 2025: PROJECTS: Power BI/Tableau Projects - Build efficient and effective data models in Power BI. Develop a range of data visualizations (to solidify my knowledge of Alteryx, QLik, Power BI, Power Query and Tableau proficiency). Create and manage relationships between different tables in data models. Write DAX formulas for advanced data manipulations and analysis within reports. A. Designed and implemented effective data models in MS Power BI, Tableau, SAS/SAS BI, R, Python and SQL. B. Effectively resolved complex programming issues and debugging challenges in Power BI/Power Query, R, Python, SAS and SQL.

2022 - 2022: Python Django Leave Requests Applications Projects - CRUD operations and Restful APIs.

2022 - 2022: I'm using Pandas Data Manipulation for exploring Hacker News (hn) datasets (Exploratory Data Analysis).

2022 - 2023: I'm using Matrix Multiplication, Normal Equation (Y= mX + C, Linear Algebra & Python), Simple Linear Regression and Scikit-Learn to predict the price of a house with a size = 3000sqft (implementing knowledge of linear algebra and python for data science).

2022 - 2023: Data Modeling in Power BI/Intermediate Data Modeling in Power BI/Data Viz (Visualization) in Power BI (Power Query Editor) and Data Viz in Tableau: Data Analysis, Visualization (Viz) and BI reporting.

2021 - 2021: Implemented XGBoost to develop Business Strategy such as estimating portfolio values and minimizing expected losses.

2021 - 2021: Extracted a number of helicopter escapees from wikepedia.org and used Python to import helper functions or csv files, explore data function, cleanse data or delete/remove duplicate data, For Loops, Conditional Statements, max function, append function, print function, matplotlib (bi/data visualization tool) and barplot function to visualize and share data insights.

2021 - 2022: Used python in jupyter notebook (ipynb) to analyze profitability in mobile applications.

2021 - 2022: Designed, documented and tested API/Restful API on Postman, SoapUI, Hoppscotch and Testim. Compared and implemented security measures on Django and Ruby website (GEO Location API vs identifier Auth0).

2007 - 2010: Collected, manipulated and analyzed data (SAS, SQL) to detect fraud and risk in income tax at South African Revenue Services .

Education

2020 - 2024: HackerRank Certify Skills/Mastery in Python*, SQL*, SAS*, R (C++, JavaScript) @ Online Certification/Courses with * means Badges already acquired (@DataCamp, DataQuest, SAS/Credly, & Udemy)

2012 - 2013: MSc in Actuarial Science @ Leicester University

2008 - 2010: BCom Quantitative Management @ University of South Africa

2006 - 2006: M.IT (Masters Degree in IT) @ University of Pretoria

2000 - 2003: BSc Applied Statistics & Operations Research @ University of South Africa

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