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Detailed Job Description:

This 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.

What kind of problems do we solve:

Our locomotives stream 350+ sensor information in real-time. We create predictive models to predict various component failures hours, days, and sometimes months in advance. There are high-frame cameras beside our tracks, capturing images of trains and rail cars as they pass. We design various Deep Learning and Computer Vision algorithms to detect certain objects of interest or issues and defects. We then optimize their performance and deploy them at the edge for real-time scoring and notification of our mechanical personnel upon detections.

What tools do we use:

We use Python, R, and Spark (PySpark, SparkR, Scala) for modeling and EDA.  You will have a local machine with 512GB of memory, so feel free to load the data in memory if it makes sense or if it fits You will also have terabytes of memory in our Spark cluster that is not shared by anyone.  We use Jupyter notebook, Emacs, PyCharm, Rstudio as IDEs.  We use Tensorflow, Keras, PyTorch, and MXNet for Deep Learning, and OpenCV for traditional Computer Vision.  You will have your own dedicated GPU in addition to a GPU cluster to run parallel training and inference jobs.  We always have the latest versions of our tools/packages/libraries available. 

What are our requirements:

Masters or Ph.D. in Computer Science, Electrical Engineering, Machine Learning, Statistics or related field, or Bachelors degree with 5+ years of industry experience Minimum of 2-3 years of relevant industry experience (as a Data Scientist, Research Scientist, Machine Learning Engineer, Computer Vision Scientist, etc.), 3+ preferred; or proven qualifications. Hands-on and theoretical knowledge of various Machine Learning algorithms and tools, e.g. xgboost/LightGBM, Random Forests, SVMs, PCA, t-sne, kmeans, DBSCAN, etc. or hands-on and theoretical knowledge of various Deep Learning algorithms and frameworks Expertise with Time Series problems is a plus Excellent knowledge of Python and/or R, knowledge of Spark is a plus

What will be your duties:

Effectively utilize appropriate statistical, Machine Learning, and Deep Learning techniques to solve various business problems Collaborate with various departments to identify opportunities for process improvement and developing analytics use-cases. Provide guidance, support and mentoring to junior team members. Evaluate accuracy and quality of data sources, as well as the designed models Stays up to date with the latest models and changes in the technology Design and develop (almost) production ready code. Communicate results to colleagues and business partners. Coordinate with application development teams to integrate developed models with existing applications.