Responsibilities: Data Analysis and Modelling: Develop and deploy machine learning and artificial intelligence models and algorithms to extract insights, predict outcomes, and optimize processes Conduct in-depth data analysis, data exploration, and data preprocessing to extract valuable information from large datasets Apply statistical techniques and hypothesis testing to validate findings Data Strategy and Planning: Collaborate with stakeholders to define data-driven objectives and formulate data strategies aligned with business goals Identify key performance indicators (KPIs) and establish data collection and measurement protocols Feature Engineering: Engineer features and create data pipelines to prepare and clean data for modelling Work with data engineering teams to ensure data availability and quality Model Evaluation and Deployment: Evaluate model performance and fine-tune models for improved accuracy Deploy models in production environments and monitor their ongoing performance Implement best practices for model version control and management Ensure proven models are integrated into business processes and software products removing the requirement for human intervention to implement the model within their respective businesses Cross-Functional Collaboration: Collaborate with business analysts, data engineers, and domain experts to understand and address specific business problems Communicate findings and insights to non-technical stakeholders in a clear and actionable manner Leadership and Mentorship: Provide leadership and mentorship to junior data scientists Participate in knowledge-sharing and training programs to enhance the data science capabilities of the team Foster a collaborative and innovative work environment Data Privacy and Compliance: Ensure data privacy and compliance with relevant regulations and best practices Develop and enforce data security protocols Requirements: Degree in Computer Science, Data Science, or a related field 4 Years experience in data science roles, including hands-on experience with machine learning, deep learning, and statistical analysis Proficiency in data analysis and machine learning tools and libraries e.g. Python, R Strong programming skills and knowledge of data manipulation and visualization Expertise in data preprocessing, feature engineering, and model evaluation Excellent problem-solving and critical-thinking skills
