Years of Experience: 7+ years, Relevant experience: 7+ years
Educational Qualification:
University degree with a strong analytical /quantitative background or equivalent experience (e.g. Data Science,Statistics, Mathematics, Econometrics, Physics, Computer Science etc.)
Role requirements:
- Strong working knowledge of Python
- Excellent analytical problem solving capabilities
- Ability to visualize and tell stories from data
- Demonstrable experience with AI, NLP and ML, preferably also statistics and coding
- Well organized and accurate with good time management, able to work independently as well as in strong dynamic teams
Responsibilities will include:
- Build machine learning models and conduct data analysis that support Springer Nature and its customers to advance discovery
- Implement and innovate cutting edge AI and data-science solutions in partnership with the wider team, sift through plenty of scientific texts and data permanently looking for the insights that help our business to move the needle
- Work in a fail-fast PoC driven environment with plenty of opportunities to move successful prototypes towards production
- Consult with stakeholders throughout the business and the Data Capability Centre
- Collaborate with other data scientists and experts as well as product-development teams on different scientific domains
- Communicate and stand in for your work and achievements, influence decisions and technologies
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