Job Description

Overview: Leading AI-driven Global Supply Chain Solutions Software Product Company and one of Glassdoor\'s \'Best Places to Work\' Seeking an astute individual that has a strong technical foundation with the additional ability to be hands-on with the broader engineering team as part of the development/deployment cycle, and deep knowledge of industry best practices, with the ability to implement them working with both the platform, and the product teams. The Platform Data Science and Machine Learning team works closely with sales, product and engineering teams to design and implement the next generation of retail solutions. Data Science team members bear the heavy burden of turning both small, sparse and massive data into actionable insights with measurable improvements to the customer bottom line. They use rigorous analysis and repeatable processes to implement both black box and interpretable models. The Data Science team uses MLOps to operationalize the machine learning pipeline. Scope: As a Data Scientist, you serve as a specialist in the engineering team that supports the team with the following responsibilities. Works closely with product and engineering teams to shape up the final solution Independently, or alongside junior scientists, implement machine learning models by Procuring data from platform, client and public data sources Prepare template notebook to demonstrate features of the solution Use data to understand patterns, come up with and test hypothesis iterate Implementing data enrichment and cleansing routines Implementing features, preparing modeling data sets, feature selection, etc. Implementing advanced statistics and analytics including segmentation, modeling, regression, forecasting etc. Evaluating candidate models, selecting and reporting on test performance of final one Apply Natural Language Processing to understand text from forum reviews, description and interactions between users Ensuring proper runtime deployment of models, and Implementing runtime monitoring of model inputs and performance to ensure continued model stability Help prepare sales materials, estimate hardware requirements, etc. Attend client meetings, online and onsite, to discuss new and current functionality Our current technical environment: Software: Python 3., NumPy, SciPy, scikit-learn, SparkML, pandas, Jupyter Notebook, Matplotlib, Azure ML Application Architecture: Scalable, Resilient, Reactive, event driven, secure multi-tenant Microservices architecture Cloud: MS Azure Frameworks/Others: Snowflake, Kubernetes, Dataflow, Kubeflow, Keras, TensorFlow, PyTorch, FastAPI What we are looking for: Bachelor\'s degree in computer science or related fields graduate degree preferred 5+ years of data science experience, retail setting preferred 3+ years of Python programming experience Strong grasp of data structures and algorithms Solid understanding of data science and machine learning foundations Familiarity with deep learning, NLP, reinforcement learning, combinatorial optimization etc. Experience working with most of the following frameworks and libraries: Pandas, Numpy, sklearn, Keras, Tensorflow, Jupyter, Matplotlib etc. Solid experience working on major cloud platforms, preferably Azure. Reasonable knowledge of modern software development tools, and respective best practices, such as Git, Jenkins, Docker, Jira, etc. Provable experience guiding junior data scientists in official or unofficial settings. Our Values If you want to know the heart of a company, take a look at their values. Ours unite us. They are what drive our success - and the success of our customers. Does your heart beat like ours Find out here: is our strategy for fostering an inclusive environment we can be proud of. Check out Blue Yonder\'s inaugural which outlines our commitment to change, and our celebrating the differences in all of us in the words of some of our associates from around the world. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability or protected veteran status.

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