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Form of workPosition:Senior Data Scientist
Job Location: 221 River Street, Hoboken, NJ 07030
Duties: Write code to develop the required solution and application features by determining the appropriate programming language and leveraging business, technical, and data requirements. Apply best practice techniques for model testing and tuning to assess accuracy, fit, validity, and robustness for multi-stage models and model ensembles. Develop advanced machine learning algorithms and leverage the latest trends in machine learning and artificial intelligence to train algorithms and apply models to new data sets. Develop deep learning-based object detection, classification, and object tracking models using Python, NumPy, Pandas, Scikit-learn, TensorFlow, Keras, PyTorch, and OpenCV. Developed scalable machine learning pipelines for data processing and model evaluation such as cross-validation, AUC-ROC, confusion matrix, precision-recall, and F1-score. Pretrain models on a massive number of high-fidelity and diverse synthetically generated images. Fine-tune models on a small sample of real data transactions to help the model adapt to real data. Guide the team on feature engineering, experimentation, and advanced modeling techniques to be used for complex problems with unstructured and multiple data sets. Contribute to code documentation, maintain playbooks, and provide timely progress updates. Develop and recommend solutions to complex business issues by translating business requirements into projects, activities, and tasks that align with the overall business strategy.
Minimum education and experience required: Master's degree or equivalent in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology, or related field and 1 year of experience in an analytics related field; OR Bachelor's degree or equivalent in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology, or related field and 3 years of experience in an analytics related field.
Skills required: Experience with Python programming and its relevant libraries, including NumPy, Pandas, Scikit-learn, TensorFlow, Keras, PyTorch, and OpenCV. Experience with data preprocessing techniques, including data cleaning, augmentation, normalization, and standardization. Experience with computer vision techniques, including image processing, feature extraction, object detection, segmentation, and tracking. Experience with synthetic data generation techniques, including physics-based simulation engines, domain randomization, texture synthesis, and GANs. Experience with model evaluation techniques, including cross-validation, AUC-ROC, confusion matrix, precision-recall, and F1-score. Experience with machine learning concepts, including supervised and unsupervised learning, clustering, regression, and classification. Experience with cloud computing platforms including AWS, GCP, and Azure for deploying and running the training and inference pipeline at scale. Experience with distributed computing frameworks, including Apache Spark, Hadoop, and Kubernetes, for scaling the training process across multiple machines or clusters. Experience with transfer learning techniques, including fine-tuning pre-trained models, feature extraction, and domain adaptation. Experience with deep learning concepts, including neural network architectures, optimization techniques, and loss functions. Employer will accept any amount of experience with the required skills.
Wal-Mart is an Equal Opportunity Employer.
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