The AI and Data Science team is a centralized team that works with various product teams across business units to define high-impact business problems, solve them using novel techniques, and execute and monitor them throughout their lifecycle. Most of our models make it to production and never sit in a research lab. However, we also do quite a bit of research to stay up-to-date with the latest technologies/algorithms.
Tools we use:
- Python, R, and Spark (PySpark, SparkR, Scala) for modeling and EDA
- Data Scientists will have a local machine with 512GB of memory
- Terabytes of memory in our Spark cluster (not shared)
- Jupyter notebook, Emacs, PyCharm, Rstudio as IDEs
- Tensorflow, Keras, PyTorch, and MXNet for Deep Learning, and OpenCV for traditional Computer Vision
- Data Scientists will have their own dedicated GPU, in addition to a GPU cluster to run parallel training and inference jobs
- The latest versions of our tools/packages/libraries
- Collaborate with various departments to identify opportunities for process improvement and developing analytics use-cases.
- Deliver advanced machine learning models to provide insights within the organization that lead to fact-based decision making.
- Effectively utilize appropriate statistical, Machine Learning, Deep Learning, and Computer Vision models and techniques to solve various business problems.
- Work cross-functionally with other IT managers to implement models in production environment
- Manage Data Scientist team and multiple projects concurrently.
- Remain up to date with the latest models and changes in the technology.
- Communicate results to colleagues, business partners, and senior management.
Job Related Experience:
- Minimum of 4-5 years of relevant industry experience (as a Senior/Lead Data Scientist, Senior Research Scientist, Senior Machine Learning Engineer, etc.), 5+ preferred.
- Experience in leading/managing direct reports and projects
- Hands-on and theoretical knowledge of various Machine Learning algorithms for regression, classification, clustering, and knowledge of various Deep Learning algorithms and frameworks for Localization, Segmentation, Object Detection, etc.
- Expertise with Time Series problems
- Excellent knowledge of Python and/or R,
- Knowledge of Spark (PySpark)
Skills and Abilities:
- Planning and Organizing
- Identifying and Considering Alternatives
- Analytical Thinking
- Effective Communication Skills