Data Scientist I

Chewy Chewy · Retail · Boston, MA

Data Scientist I at Chewy in Boston, MA, focusing on applying AI/ML methods to design, test, and scale frameworks, systems, and models for big data and predictive applications. Responsibilities include researching, implementing, and testing ML algorithms, developing ML applications, and collaborating with cross-functional teams to support new ML products. Requires a Master's degree and 2 years of experience or a Ph.D. and 1 year of experience, with skills in cloud platforms (AWS SageMaker, Snowflake), ML frameworks (PySpark, PyTorch, TensorFlow), workflow orchestration (Airflow), statistical analysis (R), data visualization (Tableau, Power BI), and CI/CD.

What you'd actually do

  1. Apply artificial intelligence and/or machine learning methods to design, test and scale effective, reliable frameworks, systems, and models to improve the usefulness of big data and predictive applications.
  2. Research, implement, and test machine learning algorithms and tools to solve data challenges and to improve quality and reliability of data.
  3. Develop machine learning applications according to requirements; design, code, test, deploy and iterate on machine learning systems.
  4. Research and remain current on machine learning and optimization techniques.
  5. Work with data scientists, application developers, product managers and software engineers to develop and support software for new machine learning products.

Skills

Required

  • Master's degree in Data Analytics, Engineering, Operations Research, Statistics, Applied Mathematics, or related field, and 2 years of experience as a Data Scientist or related position/occupation.
  • Ph.D. in Data Analytics, Engineering, Operations Research, Statistics, Applied Mathematics, or related field, and 1 year of experience as a Data Scientist or related position/occupation.
  • Cloud-based data and analytics platforms, including Amazon Web Services tools such as SageMaker, Snowflake, or other similar platforms
  • PySpark, PyTorch, TensorFlow
  • Workflow orchestration tools such as Apache Airflow
  • Statistical analysis using R
  • Data visualization and reporting using Tableau and Power BI
  • CI/CD and deployment tools
  • Programming skills for data analysis
  • Working with structured datasets
  • Collaboration with cross-functional teams to translate business requirements into scalable, production-ready analytical solutions

What the JD emphasized

  • design, code, test, deploy and iterate on machine learning systems

Other signals

  • apply AI/ML methods to design, test and scale effective, reliable frameworks, systems, and models
  • research, implement, and test machine learning algorithms and tools
  • develop machine learning applications according to requirements; design, code, test, deploy and iterate on machine learning systems
  • research and remain current on machine learning and optimization techniques
  • work with data scientists, application developers, product managers and software engineers to develop and support software for new machine learning products