Chewy is seeking early career professionals to join their software development teams to build tools and platforms that power Chewy's Data Science capabilities, enabling teams across the company to develop, test, and deploy models at scale. This involves working on infrastructure that supports forecasting, optimization, experimentation, and real-time decision-making.
Requirements
- 1–2 years of experience programming in Python, with a strong grasp of Python libraries commonly used in data science (e.g., pandas, fastparquet, pyarrow, pyspark or scikit-learn).
- Hands-on experience with AWS services for cloud-based application development.
- Proficiency with SQL and an understanding of data flows, transformation pipelines, and relational databases.
- Strong understanding of object-oriented design, data structures, and basic algorithmic thinking.
- Familiarity with modern tools used in Data Science development and MLOps (e.g., Jupyter, MLflow, Airflow, Docker, Kubernetes, Git, CI/CD pipelines).
- Experience with AWS services such as S3, Lambda, Step Functions, ECS, or SageMaker.
- Familiarity with software engineering best practices across the full development lifecycle, including coding standards, code reviews, source control management, build processes, testing, and operations.
Responsibilities
- Design and build scalable, maintainable tools and services that enable Data Scientists to run and operationalize machine learning and analytics models.
- Contribute to the development of internal platforms for simulation, experimentation, and data processing.
- Collaborate closely with Data Scientists, Engineers, and Product Managers to understand modeling workflows and optimize developer experience.
- Write clean, reliable Python code to build reusable components, APIs, and automation tools.
- Participate in creating ground breaking solutions that help Chewy remain the most trusted and convenient destination for pet parents.
Other
- Bachelor’s degree in computer science, Mathematics, Engineering, or Information Technology.
- The ability to thrive in a fast-paced environment and take accountability for your work.
- Experience working in an agile environment (e.g., Scrum, Kanban).
- A passion for enabling scientific and analytical work through thoughtful platform design.
- A proactive attitude and willingness to take on new challenges and learn from peers.
