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Microsoft Principal Data Science Manager India, Telangana, Hyderabad 194754121
17.09.2024
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Qualifications
- B.S or M.S in Computer Science or Math(PHD in Data science + ML will be a plus)
- 5+ Years of experience in deep learning (extensive work on NLP is a plus)
- 10+ Years of industry experience
- ML fundamentals: Data mining, wrangling, processing, visualization, model training, analysis.
- Expertise in Designing and hands on with Coding
- Software fundamentals: code + integrate models into production services.
- Strong knowledge and skills in machine learning software development and architectures for machine learning (with focus on deep learning).
- Research or Industry experience with one or more of following areas Natural Language Processing (NLP), Document Understanding, Information Retrieval, Natural Language Understanding.
- Experience in building, deploying, and improving large scale Machine Learning models and algorithms in real-world products.
- Proficiency in Python/C++ and deep learning frameworks e.g. Pytorch, Tensorflow.
- Ability to synthesize the research literature, compare/contrast/critique and combine ideas into creating new ML models.
- Published work in top-tier conferences & journals is a plus
Responsibilities
- Build and refine machine learning models to solve NLP tasks and productizing the solutions at scale.
- Staying abreast with the SOTA advancements and use them to formulate novel solutions.
- Advancing the state of the art of NLP technologies for real world scenarios.
- Developing novel machine learning and data mining algorithms
- Contribute ideas and techniques to shape decisions and improve product quality metrics.
- Participate in design, implementation and execution with a team of engineers, applied scientists and product managers.
- Collaborate with Program Managers, Architects and stakeholders for workforce planning, demand planning and end-to-end solution design
- Build, mentor, and lead a diverse high-performance team of Data Scientists
- Create clarity, generate energy and deliver the impact
- Ensuring compliance with Security, Privacy, GDPR etc. and performance criteria
- Use data and insights from customer and production to contribute to some technical design and implementation decisions
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