We are seeking a highly skilled Data Scientist proficient in SAS to join our data analytics team. The ideal candidate will have a strong background in statistical analysis, data mining, and predictive modelling, utilising SAS tools to drive data insights and support data-driven decision-making. This role involves working closely with cross-functional teams to develop, deploy, and optimise models that enhance business performance and efficiency. Key Responsibilities: Data Analysis and Modelling : Utilise SAS (Base, Enterprise Guide, and Visual Analytics) for data cleaning, statistical analysis, predictive modelling, and visualisation. Model Development and Deployment : Develop, test, and deploy predictive models (e.g., regression, classification) to forecast trends, customer behaviour, and other key metrics. ETL Processes : Design and maintain ETL processes to automate and optimise data flows across various systems. Data Exploration and Feature Engineering : Perform in-depth data analysis to extract patterns, identify trends, and derive actionable insights, transforming raw data into model-ready features. Performance Monitoring and Optimisation : Track and evaluate model performance post-deployment, making adjustments to ensure ongoing accuracy and relevance. Collaborative Problem Solving : Work closely with business stakeholders, data engineers, and other data scientists to understand data needs, deliver insights, and recommend process improvements. Documentation : Ensure all data science processes, models, and findings are well-documented and reproducible. Requirements: Education : Bachelor's or Master's degree in Data Science, Statistics, Mathematics, Computer Science, or a related field. Experience : 3 years in a data science or advanced analytics role, with a strong focus on SAS. Technical Skills : SAS : Proficient in SAS Base, SAS Enterprise Guide, SAS Visual Analytics, and SAS Studio. Programming : Skilled in SQL, Python, or R, with experience in data manipulation and analysis. Statistical Analysis and Modelling : Expertise in statistical methodologies, including regression, clustering, time-series analysis, and predictive modelling. Data Engineering : Knowledge of ETL processes and database management. Data Visualisation : Proficiency in visualisation tools like SAS Visual Analytics, Tableau, or Power BI. Soft Skills : Strong problem-solving skills with an analytical mindset. Excellent verbal and written communication skills. Ability to work collaboratively and independently in a fast-paced environment. Preferred Qualifications: Experience with big data technologies (e.g., Hadoop, Spark) and cloud platforms (e.g., AWS, Azure). Knowledge of other statistical tools and software. Certifications in SAS or Data Science methodologies. Benefits: Competitive salary and performance-based incentives. Professional development opportunities, including SAS certification programs. Flexible working arrangements (remote or hybrid options). Competencies: Analytical Thinking : Strong analytical skills to interpret complex datasets and generate insights. Attention to Detail : Ability to ensure accuracy and integrity of data analysis. Collaboration : Skilled in working within cross-functional teams to achieve data-driven outcomes. Adaptability : Able to work in a dynamic, evolving field with changing technology and business needs.