Are you a talented data scientist with industry experience? Are you thrilled by the opportunity to engineer robust solutions that eat real world constraints for breakfast? NetApp’s growing data science team is looking for you!
NetApp’s R&D center in Tel-Aviv is now recruiting a senior data-scientist for multiple projects: You will join a small and growing team of data scientists responsible for the entire cycle of proprietary machine & deep learning solutions.
Our solutions process huge amounts of texts in many different languages, comprehend the essence and context and provide information to the enterprise regarding sensitive information assets found in the data. We identify the most secret and secure information in the pile of millions of textual fragments, regardless of language, culture and domain.
You will research, develop and deploy machine learning pipelines that empower organizations to map and protect their most sensitive information effortlessly. The solutions you will build will be deployed into a finalized product serving thousands of companies, and protecting personal information of millions of people.
- 3+ years of hands-on machine learning experience in the industry
- M.Sc in CS / EE / exact science fields from leading universities (or B.Sc with outstanding ML engineering experience)
- Hands-on experience in back-end development (server side) / strong software engineering background, coding in python/Java/C++
- Can-do attitude and desire to become a technological focal point in the company
- Familiarity with TensorFlow / Keras / PyTorch, as well as sklearn, Jupyter and pandas
- Experience in leading large projects at the component level
- Ability to quickly prototype ideas / solutions, perform critical analysis and using creative research approaches for solving complex problems
- Experience in developing and deploying deep learning architectures at scale
- Expertise in NLP, time series and/or anomaly detection problems
- Proven experience in real world problem solving, ideally from NLP domain (e.g. encountering unexpected data, monitoring models performance after deployment and production challenges)
- Inquisitive and problem solver mentality
- Methodological with ability to break-down complex problems