Machine Learning Enginee

Role Description The Machine Learning Engineer will work part time in a remote capacity, collaborating with business development teams to design and implement data-driven solutions that support SMEs and entrepreneurs. Day-to-day responsibilities include building and training machine learning models, with a focus on pattern recognition and neural networks, to analyze business data and identify trends or opportunities. The role involves developing and optimizing algorithms, conducting statistical analyses, and preparing clear technical documentation and reports for non-technical stakeholders. The Machine Learning Engineer will also help translate business needs into data science use cases, ensure model performance and reliability, and contribute to continuous improvement of analytical tools used across BDS Hubs.

Qualifications

• Strong foundation in Computer Science and Algorithms, with the ability to design efficient, scalable solutions.
• Proficiency in Pattern Recognition and Neural Networks for building predictive and classification models.
• Solid understanding of Statistics for data analysis, model evaluation, and hypothesis testing.
• Experience with machine learning frameworks (e.g., TensorFlow, PyTorch, scikit-learn) and programming languages such as Python or R.
• Ability to work independently in a remote, part-time environment and communicate clearly with both technical and non-technical stakeholders.
• Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or a related quantitative field, or equivalent practical experience.
• Experience applying machine learning in business, finance, or SME/entrepreneurship contexts is an advantage.