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.