Senior Data Scientist

Senior Data Scientist at Micron Technology, Inc. in Boise, Idaho, United States Job Description Our vision is to transform how the world uses information to enrich life for all . Micron Technology is a world leader in innovating memory and storage solutions that accelerate the transformation of information into intelligence, inspiring the world to learn, communicate and advance faster than ever. Participate in building out and maintaining a world class finance reporting and analytics environment to provide data-based insight into key financial reporting. Work creatively on a variety of projects across a global organization with a diverse set of people. Collaborate with internal stakeholder to provide data-driven solutions to complex strategic and tactical challenges. Combine problem-solving, data-analysis, and technical skills to identify, quantify, and solve business problems. Build accurate time series, optimization, and machine learning models. Perform advanced statistical analysis. Develop and deploy end-to-end data science solutions from idea generation phase, PoC development to full productization. Drive actions and business impact through effective data presentation and data story telling. Communicate to share knowledge and findings, presenting results in a manner that the finance team and business partners can understand. Show track record of using machine learning for predictive modeling and forecasting. Demonstrate ability to take ambiguous problems and solve in a structured, hypothesis-driven, data-supported way. Use in-depth data science expertise to influence the data science lifecycle. May telecommute from home part-time. Employer will accept a Masters degree in Business Analytics, Statistics, Computer Science, or related field and 36 months of experience in the job offered or in a Senior Data Scientist -related occupation. Position also requires experience in: 1. Knowledge in concepts and implementation of AI, ML, optimization algorithms, statistics, modelling and simulation; 2. Experience with tacking and ensembling methods, model performance analysis, explainability methods, parameter search and optimization; 3. Knowledge in feature engineering, dimensionality reduction for labeled and unlabeled data sets, handling imbalance, intelligent representative sampling, data augmentation methods for numerical/image data and continuous learning; 4. Python or R; 5. ML frameworks such as TensorFlow, Keras, PyTorch, or Sci-kit learn; 6. Big data, cloud platforms and ML Ops tools and methods; and 7. SQL. As a world To view full details and how to apply, please login or create a Job Seeker account