We are hiring a Machine Learning Engineer. This role will have exposure across the entire business, influencing the vision and implementation of machine learning systems. The team uses Business Economics, Statistics, and Machine Learning techniques to understand and serve the needs of our pet parents. Developing data-driven solutions, we are an interdisciplinary team of data scientists who are committed to solving business problems using cutting edge technologies and developing data driven marketing solutions.
As part of the data science team at Chewy, you will have the opportunity to provide structure to business problems for new and existing Chewy customers by applying data science principles to design, test, implement, and develop data-based solutions, including reporting, auditing, and preparing large databases for statistical analysis. You will perform feature and behavior analysis, understand the need and fit of different ML/statistical techniques, develop the best-suited models with business intuition, validate/re-fit those models as needed, and employ them at scale.
What You’ll Do:
- 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
- Research, implement, and test machine learning algorithms and tools to solve data challenges and to improve quality and reliability of data
- 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
- Effectively resolve problems and roadblocks as they occur
- Works with data scientists, application developers, product managers and software engineers to develop and support software for new machine learning products
What You’ll Need:
- 2+ years of hands-on experience in developing and deploying optimization, predictive and machine learning model
- An advanced degree (MS or PhD) in Industrial Engineering, Operations Research, Statistics, Applied Mathematics, or equivalent quantitative fields such as Engineering, Computer Science with a background in both time series and machine learning
- Excellent verbal and written communication skills and the ability to explain details of complex concepts to non-expert stakeholders in a simple and understandable way
- Travel may be required
Bonus:
- Experience with Amazon Web Services tools such as Redshift, Snowflake, SageMaker or other similar platforms
- Experience of translating ambiguous customer requirements into clear problem definitions and delivering them
- Experience in R, PySpark, Spark, Scala, Java, PyTorch, TensorFlow, Docker
