Data Science (Machine Learning)

Responsibilities:

• Design, implement, and optimize scalable data pipelines and analytics standards to support current and future analysis.

• Design, build and optimise machine learning models for prediction at fine-grained levels of granularity.

• Select, train, retrain and deploy appropriate forecasting models per segment, adapting to changing data patterns.

• Develop, configure, and test informatics and data science solutions for diverse technical applications, while providing ongoing support.

• Monitor model performance over time and implement improvements as needed.

• Set up experiments and feedback mechanisms to ensure continuous improvement and high impact of data products.

• Collaborate closely with other data scientists to agree modelling standards, evaluation metrics and architectural patterns.

• Present findings, insights, and strategic recommendations to leadership and cross-functional teams.

• Ensure solutions are production-ready, scalable and maintainable

Requirements:

• Bachelor’s degree in engineering, computer science, finance, mathematics, or related fields.

• 5+ years of industry experience in data mining, machine learning, statistical analysis, or predictive modelling.

• Strong experience and proficiency in machine learning (ML) areas such as natural language processing, computer vision, time-series and statistical learning theory.

• Proficiency in programming languages such as Python.

• Proven experience building multi-model or many-model forecasting solutions.

• Hands-on experience with MLOps tools.

• Strong Python skills and experience with common data science and machine learning libraries e.g: TensorFlow, Pytorch, YOLO, OpenCV.

• Experience working with large-scale datasets, uncovering hidden patterns, using data visualization tools, writing SQL, and leveraging GPUs for model development.

• Fluent in English.