Data Scientist I

$100,000 - $159,000/Yr

Chewy - Bellevue, WA

Full-time - Entry Level

Bellevue, WA

1,001-5,000 employees

Sporting Goods, Hobby, Musical Instrument, Book, and Miscellaneous Retailers

About the position

The Data Scientist I position at Chewy is part of the Enterprise People Analytics (EPA) team, focused on leveraging data science and analytics to enhance HR decision-making and improve employee experiences. The role involves developing and implementing machine learning models to address real-world HR challenges, utilizing large datasets to derive insights that support workforce growth and development. The ideal candidate will contribute to a data-driven culture within the organization, collaborating with cross-functional teams to drive strategic HR initiatives.

Responsibilities

• Experiment with different machine learning techniques and tools to optimize model performance.
• Dive into massive datasets to uncover and tackle real-world challenges.
• Create impactful metrics that drive the success of HR programs.
• Collect, clean, and preprocess HR data from various sources 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 scientific methods to design, test, and scale effective frameworks and models for big data and predictive applications.
• Collaborate with cross-functional teams to support HR initiatives with data-driven insights.

Requirements

• Master's degree or equivalent experience in statistics, computer science, data science, psychometrics, or related fields.
• 1+ years of relevant experience in data science or analytics.
• Experience in deploying models into production environments and optimizing them for performance and scalability.
• Base knowledge of machine learning algorithms, both classical and modern.
• Strong problem-solving skills and a passion for learning new technologies.
• Strong grasp of descriptive statistics, probability, hypothesis testing, and regression modeling.
• Skilled in Python for 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 attention to detail.

Nice-to-haves

• Experience with GitHub, Airflow, or AWS for software development and automation.
• Proficient with data management tools like Knime or Alteryx.
• Experience with interactive data visualization tools like Plotly, Streamlit, or D3.
• Ability to translate ambiguous customer requirements into well-defined problem statements.

Benefits

• 401(k)
• Dental insurance
• Employee assistance program
• Flexible spending account
• Health insurance
• Paid holidays
• Parental leave