Job Overview: 
•    To facilitate data-driven decision-making and improve company operations, the Data Scientist will develop and execute cutting-edge AI and BI solutions
•    Drive data science projects, using sophisticated analytics and machine learning models to address difficult business challenges and generate actionable insights. 
•    They will collaborate with other departments to design data strategies, build models, and embed those models into software-driven business processes.  
 

Key Responsibilities: 
1.    Data Analysis and Modeling: - 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.  
2.    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.  
3.    Feature Engineering: - Engineer features and create data pipelines to prepare and clean data for modeling. - Work with data engineering teams to ensure data availability and quality.  
4.    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. 
5.    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.  
6.    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.  
7.    Data Privacy and Compliance: - Ensure data privacy and compliance with relevant regulations and best practices. - Develop and enforce data security protocols.  
 

Qualifications:
    Bachelor's or Master's degree in computer science, data science, or a related field. 
    Proven experience in data science roles, including hands-on experience with machine learning and statistical analysis. 
    Proficiency in data analysis and modeling tools and libraries e.g. Python and 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. 
    Strong communication and interpersonal skills to effectively collaborate with various stakeholders. 
    Relevant certifications e.g. Certified Data Scientist etc. are a plus.