Appriss Retail is looking to maximize profitability while managing risk for its customers, and the Data Scientist role is expected to contribute to this goal by building, maintaining, and enhancing production-level data infrastructure.
Requirements
- Proven track record of writing production-ready Python and SQL code.
- Familiarity with common data and ML libraries (e.g., dbt, pandas, NumPy, scikit-learn).
- Strong SQL skills and experience with large, complex datasets.
- Experience in end-to-end data project delivery—from code development to deployment.
- Familiarity with version control (Git) and collaborative coding workflows.
- Strong understanding of software engineering principles in a data science context.
- Experience with statistical modeling, machine learning, and A/B testing.
Responsibilities
- Write, maintain, and optimize production-level Python and SQL code for data pipelines, MLOps workflows, and related systems.
- Analyze structured and unstructured datasets to identify trends, patterns, and opportunities for improvement.
- Design, implement, and maintain automated data ingestion, transformation, and validation pipelines.
- Contribute to the design, testing, and deployment of predictive and prescriptive models.
- Support deployment of pipelines and ML models, including standing up and managing relevant cloud infrastructure.
- Collaborate with engineering, product, and business teams to translate requirements into scalable, code-driven solutions.
- Apply rigorous statistical and software engineering best practices to ensure accuracy, reproducibility, and reliability.
Other
- Master’s Degree in Computer Science, Data Science, Statistics, Mathematics, or related field (Bachelor’s degree with significant relevant experience considered).
- Ability to communicate technical concepts clearly and effectively.
- Commitment to producing high-quality, maintainable, and scalable code.
- Travel requirements not specified
- Six months temporary role with possibility of extension
