Michael Darko Ahwireng

Data Engineer


I am an aspiring Data Engineer with over 3 years experience of working with spatial data and willing to work within time zones different from that of my location and provide liability and data breach insurance from a US company when needed. I am experienced in Python, SQL, JavaScript, HTML and CSS. I have completed Big-Data projects with Kafka, Airflow and Spark . I aspire to contribute his knowledge and skills in analytical and systematic problem- solving techniques to and learn from a progressive corporate environment in which these skills are relevant and appreciated. I love cats, soccer and babies.


Work Experience

GIS Analyst/Hydrogeologist  •  Aqualogical Technologies Limited

March 2018 - June 2021

- Led in the acquisition and analysis of satellite images for the selection of the best point for drilling boreholes using Python and ENVI.
- Created maps and geodatabase using ArcGIS, QGIS, Postgres, and PostGIS for reconnaissance surveys and built projects
- Planning and leading geophysical surveys.
- Supervised construction of 2 water systems and more than 100 boreholes


10 Academy

Machine Learning and Data Engineering

2021 - 2021

Worlquant University

Python Programming, Statistical Data Analysis and Machine Learning

2019 - 2020

University of Ghana

MSc GeoInformation Science

2019 - 2020

University of Ghana

BSc Earth Science

2010 - 2014


Flower Image Classifier

Used VGG as a pretrained network to build a new feed-forward network as a classifier using ReLU activations and dropout. The built model can be trained with any set of labeled images. This was done with Pytorch.

Water Flow Modeling

Used pdal and geopandas to build a custom module to interact with ept and lidar files and extract information to build the Digital Elevation Model and create Topographic Wetness Index from the DEM.

Corona Virus Tweet Analysis

Used gensim as a base for natural language processing and streamlit as a means of displaying findings. Scikit-learn was used to build a tweet classifier as well.

Causal Inference on Breast Cancer Data

Performed causal inference on the variables recorded to influence the diagnosis of tumor to be malignant or benign. Machine Learning was merged with causal inference by using XGBoost to extract the important feature on which the causal inference was made.


   JavaScript      ArcGIS      Python      kafka      Spark      dbt      DVC      Scikit-Learn      PyTorch     Airflow


   English — Native or Bilingual      Akan — Native or Bilingual   

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