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.
#J-18808-Ljbffr