Data Scientist I

We are hiring incredible humans, and we hope that includes you!

Are you looking for more than just a job? At Chewy, you’ll find yourself on a career path with other outstanding humans, like yourself. You’ll be part of a culture that values everything that you do, who you are, and the goals you have set for your career. We want to give you the opportunity to grow, earn competitive pay, and be happy while you, do it. Sounds simple, but we love it.

Your Opportunity:

We are looking for a Data Scientist within Chewy’s Enterprise People Analytics (EPA) team located in Bellevue, WA or Boston, MA. This is a dynamic and innovative organization dedicated to encouraging a data-driven culture within our HR department. Our People Analytics team uses data and analytics to drive strategic decision-making, improve employee experience, and support the overall growth and development of our workforce.

The EPA team is committed to revolutionizing the employee experience by harnessing the power of data and analytics. With a focus on analytics, data science, machine learning, and AI, we aim to anticipate workforce trends, optimize talent management practices, and create personalized experiences that empower employees to thrive. Through collaboration, visibility, and ethical data practices, we envision a future where data-driven HR transforms every aspect of the workplace, driving sustainable growth and success for Chewy and its employees. 

Within this role you will use data science principles to develop, implement, and refine machine learning models and algorithms that tackle real-world problems. The ideal candidate will showcase a portfolio or examples of their work that have been successfully implemented in a production environment.

 What You’ll Do:

• Experiment with different machine learning techniques and tools to optimize model performance.
• You will dive into extensive datasets, uncover and tackle real-world challenges, and create impactful metrics and business cases that drive the success of this program.
• The ideal candidate will take a customer-first approach to uncover insights and pinpoint actions that can enhance the customer experience and boost program conversion.
• Collect, clean, and preprocess HR data from various sources (e.g., AWS, Snowflake) to ensure data quality and integrity
• Conduct exploratory data analysis to identify trends, patterns, and anomalies in HR data
• Develop and implement statistical models and algorithms to analyze employee data, including turnover, engagement, and performance ratings
• Apply science methods to design, test, and scale effective, reliable frameworks, systems, and models to improve the usefulness of big data and predictive applications
• Collaborate with cross-functional teams to support HR initiatives and projects with data-driven insights

What You’ll Need:

• Master’s degree or equivalent experience in statistics, computer science, data science, psychometrics, or related fields
• 1+ years of experience in the relevant filed
• Experience in deploying models into production environments and optimizing them for performance and scalability
• Base knowledge of machine learning algorithms, both classical (e.g., regression, decision trees) and modern (e.g., deep learning, reinforcement learning)
• Strong problem-solving skills and a passion for learning and applying new technologies
• Strong grasp of descriptive statistics, probability, hypothesis testing, and regression modeling
• Skilled in Python, data workflows including tidying, wrangling, visualization, modeling, scripting, and reporting
• Competent in SQL for data extraction and manipulation, including complex joins and common table expressions
• Proficient in statistical and machine learning techniques, with a strong attention to detail and a passion for data
• Proficient in developing dashboards using BI tools like Tableau, Power BI, Looker, or similar platforms
• Excellent team collaboration skills paired with effective communication abilities to simplify complex concepts for non-expert collaborators

Bonus:

• Use GitHub, Airflow, or AWS for software development and automation
• Proficient with data management tools like Knime or Alteryx
• Applied Plotly, Streamlit, or D3 for interactive data visualization and presentation
• Translated ambiguous customer requirements into well-defined problem statements and delivered solutions effectively