Description

You will build and deploy machine learning models to solve complex data problems.

Responsibilities

• Build hands-on machine learning models, specifically focusing on demand forecasting at scale.
• Deploy and monitor ML models in production to deliver data products to end-users.
• Manage ML CI/CD pipelines to ensure reliable model delivery.
• Optimize GPU code and Spark MLlib performance.
• Apply statistical modeling techniques including hypothesis testing, sample size estimation, and A/B testing.

Required Skills

• 14+ years of experience in data science and hands-on ML model development.
• Expertise in demand forecasting at scale.
• Proficiency in Python, R, and SQL.
• Experience with Spark and Spark MLlib.
• Deep knowledge of ML frameworks including TensorFlow, Keras, and PyTorch.
• Experience with cloud computing services such as AWS, GCP, or Azure.
• Expertise in Regression, Classification, Clustering, Time Series Modeling, Graph Networks, Recommender Systems, Bayesian modeling, Deep Learning, Computer Vision, NLP/NLU, Reinforcement Learning, Federated Learning, and Meta Learning.
• Technical proficiency in Decision Trees, Random Forests, KNN, SVM, ANOVA, PCA, Gradient Boosted Trees, ANN, CNN, RNN, and Transformers.
• Bachelor's, Master's, or PhD in a quantitative field like CS, Machine Learning, Mathematics, Statistics, or Data Science.

Preferred Skills

• Experience within the retail industry.

Key Skills

Education

Bachelor's /Master's /PhD degree