URBN is hiring a Senior Data Scientist to join the Data Science organization who is responsible for building, deploying, and maintaining Machine Learning systems to support the URBN brands. Our expertise spans project management, machine learning, software engineering, data engineering, and analytics. Unlike most Data Science organizations, our team is a full-service Machine Learning solution provider, taking projects from ideation and requirements through deployment of production services. We work closely with the Engineering teams on a wide range of projects including an in-house personalization system, demand forecasting, price optimization, and warehouse optimization.
The Senior Data Scientist role requires strong technical knowledge of data science and machine learning best practices and the ability to analyze complex data. This individual will play a critical role in executing tasks in the timely execution of tasks and delivering work toward the team’s data science projects.
Role Responsibilities ML Modeling: Evaluate and build statistical and machine learning models with an emphasis on business impact and time-to-production. Approaches span from basic regressions to advanced neural networks.Analysis: Support opportunities to add value to the business through application of statistical and ML techniques. Quantify the impact of those opportunities and communicate the outcome to peers and leaders.ML Deployment: Support ML engineers in deploying data science algorithms in production. This includes containerizing algorithm training and inference workflows, building data pipelines, and monitoring already-deployed ML systems. Role QualificationsMasters or PhD degree in Computer Science, Analytics, Data Science, Mathematics or related field or equivalent job experience
At least 4 years of job experience in a data science role Experience in training, testing and troubleshooting ML modelsStrong experience with multiple ML models (e.g., logistic regression, XGBoost, clustering, neural networks, LLMs, forecasting)Strong experience in data wrangling, cleaning and feature engineering to create ML-model ready datasetsStrong statistical and analytical skills (e.g., t-tests, nonparametric tests, data distributions) Strong Python experience, familiarity with SQL Proficient in state-of-the-industry ML tools and libraries (e.g. scikit learn, Jupyter Notebooks, TensorFlow, pyTorch, etc.)Understanding of fundamental Machine Learning concepts, including: train/dev/test sets, overfitting, scoring metrics, etc.Experience using ML approaches on real-world applicationsContainerization (Docker)Experience working with Cloud platforms (Google Cloud Platform, etc.) is a plusExperience with Cloud infrastructure (Virtual Machines, Cloud Storage, etc.) is a plusExperience with Performance evaluation of deployed, customer-facing applications and ML models is a plusExperience with Data or ML orchestration frameworks (MLflow, Airflow, etc.) is a plus
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The PerksURBN offers comprehensive Perks & Benefits to employees. Availability and eligibility to specific benefits may be subject to your location and employment status. Benefits include medical, dental, vision, PTO, generous employee discounts, retirement savings and much more! For additional information visit www.urbn.com/work-with-us/benefits
EEO StatementURBN celebrates diversity and is committed to creating an inclusive environment for all employees. We are proud to provide equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, sex (including gender, pregnancy, sexual orientation, and gender identity or expression), religion, creed, age, physical or mental disability, national origin or ancestry, ethnicity, citizenship, service in the uniformed services, genetic information, or any other protected characteristic as established by law. We believe strongly in fostering a safe, fair and respectful work environment. To ensure compliance with our non-discrimination and anti-harassment policies, we offer anti-harassment training to managers and employees. Options ApplyApplyShareSubmit a ReferralRefer Sorry the Share function is not working properly at this moment. Please refresh the page and try again later. Share on your newsfeed Not finding the perfect fit?
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