Job title: Senior Software Engineer- Data Science
Job description: Job Description : Are you looking for work in the most interesting business in Microsoft? Do you want to help deliver quality Line of Business applications on the latest Microsoft technologies to help the SUPPLY CHAIN BUSINESS SOLUTIONS, which manag
Job Description : Are you looking for work in the most interesting business in Microsoft? Do you want to help deliver quality Line of Business applications on the latest Microsoft technologies to help the SUPPLY CHAIN BUSINESS SOLUTIONS, which manages the businesses of manufacturing and supply chain (MSC) for XBOX, KINECT, HOLOLENS and SURFACE in its mission to produce the world’s best entertainment systems? Are you excited about enhancing your research by applying it to real life problems, building world-class software, working on data/algorithms, learning, having fun and maintaining work-life balance? SUPPLY CHAIN BUSINESS TECHNOLOGIES is a global Engineering team that delivers Line of Business applications to support rapid growth of our business. Currently there are 100+ applications in our portfolio and these include revenue systems, forecasting and planning, returns & refurbishment, sales, business intelligence and much more based on core Microsoft platforms including Azure, SQL, BizTalk, MS Dynamics AX and more. The application portfolio is largely based on Supply chain operations reference (SCOR) model comprising of 5 distinct management processes namely – Plan, Source, Make, Deliver and Return. Application portfolio also includes third party products like SAP R/3, APO etc. We engineer applications from the ground up specific to the requirements of the business, and we need people who are passionate about delivering a high-quality bar into production. In your journey with Microsoft, you will be applying your computer science skills to innovate, design and implement solutions for cutting edge web scale problems. You will also get an opportunity to work on Big Data and employ ML techniques in the supply chain ecosystem. Our team comprises of highly motivated researchers, engineers, product managers and data-scientists building end-to-end web-scale and enterprise-scale AI systems. Together we develop and deliver robust, state of art and scalable solutions across a rich set of scenarios. Develop highly scalable classifiers and tools leveraging machine learning, data regression, and rule-based models, deep learning Create language models from petabytes of text data in different languages Suggest, collect and synthe requirements and innovate to create next generation feature sets Work as part of the product team to implement algorithms that power user and developer-facing products reaching out to millions of users. Be responsible for measuring and optimizing the quality of your algorithms and Models Adapt standard machine learning methods to best exploit modern parallel environments bs/ms degree in computer science or related quantitative field with 4-8 years of relevant experience strong background in one or more of machine learning, artificial intelligence, pattern recognition, natural language programming, deep learning, dnns, large scale data mining experience with scripting languages such as perl, python, php, and shell scripts experience with recommendation systems, targeting systems, ranking systems or similar systems experience with any of hadoop/hbase/pig or mapreduce/bigtable or r/matlab/azureml or similar technologies ph d degree in computer science or related quantitative field is a plu experience in analyzing very large real world datasets and hands-on approach in data analytics experience with test driven development, continuous integration, continuous deployment, telemetry etc. great design and problem solving skills, with a strong bias for quality and engineering excellence excellent verbal and written communications skills excellent problem-solving and debugging skills with a solid understanding of testing practices
Location: Hyderabad, Telangana – Secunderabad, Telangana
Job date: Sun, 10 Jan 2021 23:45:43 GMT
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