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| Job Location | Noida |
| Education | Not Mentioned |
| Salary | Not Disclosed |
| Industry | IT - Software |
| Functional Area | General / Other Software,Sales / BD |
| EmploymentType | Full-time |
Job summaryMarkets across world, supporting custom wide features for the emerging markets (Middle East, Australia, Singapore, Turkey, Brazil to name few) and creating new features to enable cross country product selection, purchase and fulfillment features to enable Amazon exports in the world. The team takes care of technology business needs of these markets end to end and key functions range across marketing, pricing, Delivery Experience, Customer Experience, finance of these marketplaces.AEE is looking for an Applied scientist who will build ML capabilities in the MENA and other emerging markets. Currently the team is working on wide range of ML problems starting from predicting Customer lifetime churn and Prime Subscription churn, forecasting best pricing to offer new selection, profitability programs like MOQ (minimum ordered quantity), price elasticity. Team is also building delivery experience related models to solve the unstructured address data problems in MENA and other geographies and score these addresses for quality. An ideal candidate will be an expert in the areas of optimization, machine learning and statistics, with expertise in applying theoretical models in an applied environment. The candidate will be expected to work on numerous aspects of Machine Learning such as feature engineering, predictive modeling, probabilistic modeling, hyper-parameter tuning, scalable inference methods and latent variable models including transfer learning. Challenges will involve dealing with very large data sets and requirements on throughput. Researching, designing, implementing, testing, deploying, and maintain innovative models and machine learning solutions to accelerate our business and customize the customer experience. Creating experiments and prototype implementations of new learning algorithms and prediction techniques Produce peer-reviewed research reports reaching the same level of correctness, scholarliness, usefulness, completeness, depth and rigor and/or originality as a respected peer-reviewed external publication. Where appropriate, you submit to internal and external publication venues Participate in team design, scoping and prioritization discussions Use machine learning best practices to ensure a high standard of quality for all of the team deliverables, Masters in Computer Science, Machine Learning, Operations Research, Statistics or a related quantitative field 3+ years of hands-on experience in predictive modeling and analysis 2+ years of hands-on experience in Python, Perl, Scala, Java, C#, C++ or other similar languages 1+ years of professional experience in software development Proficiency in model development, model validation and model implementation for large-scale applications Ability to convey mathematical results to non-science stakeholders Strength in clarifying and formalizing complex problems Superior verbal and written communication and presentation skills, ability to convey rigorous mathematical concepts and considerations to non-experts PHD with hands-on experience applying theoretical models in an applied environment Significant peer reviewed scientific contributions in relevant field Strong fundamentals in problem solving, algorithm design and complexity analysis Strong personal interest in learning, researching, and creating new technologies with high commercial impact Experience with defining organizational research and development practices in an industry setting Proven track in leading, mentoring and growing teams of scientists
Keyskills :
predictive modelingcommercial modelsoperations researchcalibrationdocumentationapihplcmachine learningalgorithm designmodel validationemerging marketsresearchmodel developmentresearch development