Senior SAS Developer & Data Science Engineer
Summary
Designs, builds, and optimizes SAS ETL workflows, macros, and automated processes while developing predictive and statistical models using SAS plus Python or R. Works with large structured/unstructured datasets and delivers insights via dashboards and reports. Onsite in Halifax, Canada.
The SAS Developer will be responsible for designing, developing, and optimizing advanced data-driven solutions by leveraging strong SAS programming and modern data science techniques. This role involves building ETL workflows, performing predictive analytics, creating statistical models, and delivering actionable insights to support business decision-making. The ideal candidate will work with large datasets, collaborate with stakeholders, and ensure high data quality, transparency, and analytical rigor.
Key Responsibilities:
- Design, develop, and maintain SAS ETL programs for data extraction, transformation, and loading.
- Create optimized SAS macros, stored processes, and automated workflows.
- Ensure data integrity, accuracy, and compliance with organizational standards.
- Perform exploratory data analysis (EDA) and feature engineering for model development.
- Build predictive models using SAS along with Python or R.
- Apply statistical modeling, machine learning, and advanced analytics to business challenges.
- Interpret and present insights through dashboards, reports, and visualizations.
- Work with structured and unstructured datasets from multiple sources.
- Implement data quality checks and governance frameworks.
- Partner with business stakeholders to translate requirements into technical solutions.
- Document all data processes, workflows, and models for transparency and reproducibility.
- 8+ years of experience with SAS Base, SAS Macro, SAS SQL, and SAS Enterprise Guide.
- 8+ years of hands-on experience with Python or R for data science tasks.
- Strong knowledge of machine learning algorithms and predictive modeling.
- Experience with large datasets, SQL databases, and data warehousing concepts.
- Familiarity with visualization tools such as Power BI or Tableau.
- Strong analytical, problem-solving, communication, and documentation skills.
- Ability to work with complex data from multiple systems.
- Experience in healthcare, finance, or insurance analytics.
- Knowledge of cloud platforms (AWS, Azure, GCP) and big data technologies (Hadoop, Spark).
Bachelor’s or Master’s degree in Computer Science, Statistics, Data Science, or a related field.