CV

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Bright Aboh

*** ********** **, *** ******, DE

Æ 302-***-****

R ad3gby@r.postjobfree.com

https://brightaboh.github.io

https://github.com/BrightABOH

linkedin/brightaboh

Skills

Python(Pandas, Numpy,

Matplotlib, Sci-kit learn,

Jupyter-notebook)

5+ yrs

Machine Learning /

Deep Learning

4+ yrs.

SQL 3+ yrs.

Linux/Mac OS 5+ yrs.

Scala 4+ yrs.

R 4+ yrs.

ML-flow 2+ yrs.

Software

Cloud computing(AWS) 2+ yrs.

Cloud computing(Google

Earth Engine)

2+ yrs.

Version control(git) 3+ yrs.

Language

English L1

French C2

About me

I am a passionate and results-driven data scientist with a strong background in predictive modeling, deep learning, and machine learning. My journey in the world of data began with a fascination for uncovering insights hidden within complex datasets, and it has evolved into a commitment to leveraging cutting-edge technologies to solve real-world problems.

Work experience

Machine Learning Expert - International Consultant 08/2023 - Present ACCIONA SA

Remote

Detailed achievements:

• Applied PyTorch for training deep learning models dedicated to boundary delineation and crop type classification, achieving outstanding results on all metrics measured.

• MLOps for End to End model deployment into a web application

• Conducted comprehensive automation of data processing and preparation procedures, optimizing efficiency by reducing repetitive processing time by 70%.

• Conducted comprehensive training sessions for National Institute of Statistics Rwanda staff, focusing on machine learning design, pipeline development, and code documentation.

Technical Data analyst 05/2023 - 12/2023

Affiliated Distributors

Wayne

Detailed achievements:

• Leveraged python for advanced e-commerce product analytics and process automation, showcasing versatility in data-driven decision-making and opti- mization strategies for A/B testing.

• Contributed to decision-making processes by presenting clear and data-driven assessments, empowering the Digital Content Manager to make informed choices regarding AI product adoption.

• Collaborated with the Digital Content Manager to devise algorithms automat- ing e-commerce data quality procedures, leading to an impressive 95% de- crease in manual checks.

• Proficient in utilizing SQL for efficient retrieval and ingestion of large datasets, demonstrating a robust foundation in database management. CV

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Interests

Statistical modelling

Image recognition

Regression analysis

Predictive modelling

Data manipulation/data analysis

Dashboard development

Effective documentation and com-

munication

Research

Education

08/2017 - 02/2019

Mathematical Sciences (M.Sc.)

African Institute for Mathematical

Sciences

09/2018 - 10/2018

Short courses on applied math-

ematics: Data science and net-

works

Technische Universität Chemnitz

09/2011 - 07/2015

Financial Mathematics (B.Sc.)

University for Development Studies

Data Scientist 09/2021 - 04/2023

Philip Morris International

Remote

Detailed achievements:

• Innovatively designed algorithms to identify crop types from Synthetic Aper- ture Radar (SAR) images, showcasing expertise in image analysis and pattern recognition.

• Proficient in model training using Amazon SageMaker and ML flow, lever- aging cloud-based solutions for scalable and efficient machine learning/deep learning workflows.

• Engineered a state-of-the-art deep learning segmentation model, achieving an impressive 85% precision in delineating land parcels.

• Conducted comprehensive code review and documentation. Data science consultant 04/2021 - 08/2021

Ghana Statistical Services

Ghana

Detailed achievements:

• Mentored and trained a cohort of 6 Data Science Trainees from the Ghana Statistical Service, providing hands-on guidance in dashboard development using Python and plotly Dash.

• Led comprehensive data pre-processing initiatives, ensuring the integrity and quality of datasets for accurate and impactful analysis.

• Developed and deployed an interactive dashboard for real-time monitoring of Ghana’s Population and Housing Census, contributing to data-driven decision-making.

Research assistant 11/2020 - 04/2021

UK-Research and Innovation/AIMS

Rwanda

Detailed achievements:

• Developed a comprehensive methodological framework for modeling air pol- lution in Sub-Saharan African cities, laying the foundation for robust and accurate analyses in environmental research.

• Fostered collaborative efforts by conducting regular meetings with profession- als from Imperial College and Universities Space Research Association. These engagements focused on the exchange of knowledge and in- sights related to data analytics and advanced methodologies, contributing to a dynamic and informed research environment.

• Evaluated the potential for merging ground-level and satellite sensing tech- nologies with data analytics and AI methods to enhance data-driven decision- making

CV

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Data scientist (Machine learning researcher) 06/2019 - 09/2020 Rwanda Environment Management Authority

Rwanda

Detailed achievements:

• Demonstrated proficiency in Google Earth Engine mapping and implementa- tion of machine learning models on satellite imagery, including Landsat 7, 8, and MODIS. Implemented classification models such as SVM, CART, and Decision Trees for precise land use and change detection.

• Analyzed air quality data from stationed RAMPs (Real-time Air Quality Mon- itoring Platforms) to provide valuable health recommendations, showcasing a holistic approach to data-driven insights.

• Spearheaded a team of 12 members in Rwanda’s national satellite data col- lection initiative, spanning seven governmental departments. Achieved a re- markable 75% reduction in data collection time for Land Use assessments.

• Successfully established and managed a PostgreSQL database, showcasing strong database management skills.

Publications

• B. Aboh. Satellite imagery analysis for land use, land use change and forestry: A pilot study in kigali, rwanda. 2020

Presentations

Crop type clustering using NDVI

Data Science Conference, Europe September,2022

Location: Belgrade/Virtual

Satellite Imagery Analysis for Land Use, Land Use Change and Forestry : A Pilot Study in Rwanda

NeurIPS 2020 Workshop: Tackling Climate Change with Machine Learning June,2020 Location: Virtual

Satellite Imagery Analysis for Land Use, Land Use Change and Forestry : A Pilot Study in Rwanda

ACM SIGCAS Conference on Computing and Sustainable Societies September,2020 Location: Virtual

Contact this candidate