Sas Data Scientist
4 weeks ago
**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.
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