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We are looking for an Associate Director, of Data Science at our facility in Richardson, TX to design and implement best-in-class data solutions best suited to deliver on our needs and use cases.
What You’ll Do:
- Apply machine learning capabilities and best practices that can analyze large volumes of structured and unstructured data to produce reliable insights and decision-making.
- Improve upon existing time-series forecasting and optimization models with greater precision and accuracy.
- Build and improve classification and segmentation modeling for customers as well as create survival analysis studies for customer churn.
- Provide thought leadership by recommending the right technologies and solutions for a given use case, from the application layer to infrastructure; and have the leadership and coding skills (e.g. Python, SQL) to get solutions into production while ensuring performance, security, scalability, and robust data integration.
- Collaboratively drive success and communicate insights for identifying new areas of opportunities that will drive Chewy’s value and growth goals forward; coordinate with the stakeholders to prioritize and lead the changes to production.
What You’ll Need:
- Master’s degree in Engineering, Mathematics, Computer Science, Statistics, or a related field and 4 years of experience.
- Alternatively, a PhD and 2 years of experience.
- Experience must involve 2 years of experience as a Software Engineer or Data Scientist.
- Experience must also involve the following: Python programming and data pipeline best practices;
- Applied machine learning and NLP at scale, including Bayesian modeling, regression, dimensionality reduction,
factor analysis, TFIDF, topic modeling, and support vector machines;
- Model evaluation, hyperparameter tuning, and feature engineering techniques;
- Programming experience in Python, Scala, or another modern programming language; and
- SQL and the ability to write, debug, and optimize SQL queries.
- The position is eligible for the Employee Referral Program.