Machine Learning Engineer - Dataware Tech Ghana

Dataware is an award-winning company on a mission to assist organizations in Africa gain insights from data for strategic decision making on the go. Our rapidly growing company is looking for a motivated individual to fill the role of MACHINE LEARNING ENGINEER. The employee will work closely with the Chief Technology Officer to develop and implement solutions for projects.

The primary role of the Machine Learning Engineer is to discover trends in data sets, design and develop algorithms that will be specific to providing insights related to clients’ business goals or objectives. Aligning data sets to clients’ objects is key to the performance of this role.

Some responsibilities will be:

• Design and develop the end-to-end solution for the deployment of dashboards and reports to various stakeholders
• Work directly with the business teams to rapidly prototype analytics solutions based upon business requirements
• Architect data pipelines and ETL processes to connect with various data sources
• Deploy sophisticated analytics programs, machine learning and statistical methods
• Prepare data for predictive and prescriptive modelling

• Use data to discover tasks that can be automated
• Design and maintain enterprise data warehouse models
• Tune and improve the performance of reporting solutions
• Manage cloud-based data & analytics platforms (MS Azure, AWS, and Dell Platforms)
• Create Semantic Data Models as the foundation for self-service enterprise reporting
• Other duties that may be assigned by Supervising or Senior Officers

What are the requirements?

• Bachelor’s/ Master’s degree in computer science, data science, mathematics, or a related field.
• At least two years of experience in delivering high-quality machine learning models for the production environment (Preferably Python).
• Proficient with Python and R code writing.
• Extensive knowledge of ML frameworks, libraries such as sklearn, pandas, numpy, Pytorch and TensorFlow.
• Demonstrated excellence in building, scaling, and productizing machine learning models with the best MLOps best practices in mind.
• In-depth knowledge of mathematics, statistics, and algorithms.
• Analytical, problem-solving abilities and team player.
• Great communication and collaboration skills.
• Excellent time management and organizational abilities.