Our Opportunity:

We are looking for a Machine Learning Engineer II at our facility in Minneapolis, Minnesota, to research, design, and implement predictive models, use data sciences to detect and prevent high risk fraud and reduce false positives.

What You’ll Do: 

• Work across all stacks of the Machine Learning model lifecycle from data preparation and processing to deployment.
• Work with fraud team and trust SMEs to understand domain knowledge, business expectation and turn them into data driven machine learning approach.
• Develop machine learning, data mining, statistical, and graph-based algorithms designed to analyze massive data sets; partner with Cloud technologists to ensure proper implementation and usage of said algorithms.
• Analyze large data sets to develop multiple, custom models and algorithms to drive innovative correlations for fraud and acceptance data as well as social data.
• Ideate, brainstorm and drive projects from conception to completion.
• Conduct exploratory data analysis, supervised, unsupervised and semi supervised machine learning to identify fraud trend, segment and clusters, and optimization opportunity.
• Lead identification of trends and KPI’s with the objective of improving customer performance.

What You’ll Need:

• Master’s degree in Engineering, Mathematics, Physics, Finance, Computer Science, or a related field and 2 years of experience.
• Will accept a Bachelor’s degree and 5 years of experience.
• Experience must include: perform data mining tasks including data exploration, data cleaning, factor generation/selection, and data visualization to support large scale Data Science initiatives;
• develop web applications that enable business owners to interact with developed models or results;
• business, technology, manufacturing processes and data science related topics such as data systems (data sources, data gathering, storing) and business analytics (business reporting procedures and KPIs);
• develop web applications using Java, C#/.Net;
• HTML, CSS, JavaScript;
• machine learning/deep learning algorithms using Python, Pyspark over ML platforms such as Jupyter, Spyder and Sagemaker;
• data engineering platforms such as Apache Spark, Hive, Scala, Yarn;
• ETL tools like Ambari, Airflow, SSMS and SSIS.
• The position is eligible for the Employee Referral Program.

Chewy is committed to equal opportunity. We value and embrace diversity and inclusion of all Team Members. If you have a disability under the Americans with Disabilities Act or similar law, and you need an accommodation during the application process or to perform these job requirements, or if you need a religious accommodation, please contact CAAR@chewy.com.

If you have a question regarding your application, please contact HR@chewy.com.

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