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- Tasks: Research and develop algorithms for Mendeley's software tools to enhance research collaboration.
- Company: Join Elsevier, a leader in innovative technology transforming global research practices.
- Benefits: Enjoy a dynamic work environment with opportunities for remote work and professional growth.
- Why this job: Be part of a mission-driven team making a real impact in the research community.
- Qualifications: MSc or PhD in Computer Science; experience with NLP, Machine Learning, and Java required.
- Other info: Fluent English is essential; strong presentation skills are a plus.
The predicted salary is between 36000 - 60000 £ per year.
Elsevier is in the midst of a transformation and technology is simultaneously at the forefront and the driving force. Our innovative technology platforms and smart content solutions operate at the cutting edge of big data, semantic web and cloud technology, enabling faster more effective critical decision-making daily across the globe. Product Mendeley is part of Elsevier. Mendeley is changing the way research is done. We are mission led with a strong commitment to providing the best tools to help researchers and scientists do their work. We’ve built a global research collaboration platform, reference management tool and open research database.
The Role
We are looking for a Data Scientist whose main responsibilities are to research, develop and evaluate algorithms in order to build software tools for researchers. You will contribute to building systems that help researchers to organise their research, contextualise it with respect to other research, collaborate with one another, and discover new research.
Responsibilities:
- Research, develop and evaluate algorithms for use in Mendeley’s software tools
- Demonstrate how well these algorithms perform when applied to real data
- Work with engineering teams to deliver algorithms in production environments
What you’ll be doing
- Identify, obtain and prepare data sets for training and testing algorithms
- Research, develop and evaluate algorithms for systems such as recommender and information extraction systems
- Build proof of concept prototypes demonstrating these algorithms in action
- Evaluate algorithms through controlled offline and online experiments
- Work with engineering teams to guide prototypes through to production, making reliable/scalable systems
- Manipulate large scale data (data cleaning, data normalisation, data linkage)
Qualifications:
- Strong research and development experience in industry and/or academia
- Hold an MSc, preferably PhD, in Computer Science
- Experience working with large graph/network data sets, with rich textual content
- Experience of Java programming; can independently prototype solutions to problems
- Experience with Recommender System, NLP and Machine Learning libraries
- Experience with big data technologies (e.g. Hadoop, MapReduce, Cascading, Scalding, Scala) is desirable but not required
- Unix skills
- Experience with start-up and R&D environments
- Strong presentation skills in communicating with experts and novices
Language requirements: Fluent spoken and written English
Educational level: Master Degree
Data Scientist – PhD Computer Science, Recommender Systems, NLP, Machine Learning, Java employer: NLP PEOPLE
Contact Detail:
NLP PEOPLE Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Scientist – PhD Computer Science, Recommender Systems, NLP, Machine Learning, Java
✨Tip Number 1
Familiarise yourself with the latest advancements in recommender systems and NLP. This will not only help you understand the role better but also allow you to engage in meaningful conversations during interviews, showcasing your passion and knowledge.
✨Tip Number 2
Network with professionals in the field of data science, especially those who have experience with Mendeley or similar platforms. Attend relevant meetups or webinars to build connections that could lead to referrals or insider information about the company culture.
✨Tip Number 3
Prepare to discuss your experience with large graph/network data sets and how you've applied machine learning algorithms in past projects. Be ready to provide specific examples that demonstrate your problem-solving skills and technical expertise.
✨Tip Number 4
Showcase your ability to work collaboratively by highlighting any previous experiences where you successfully partnered with engineering teams. This is crucial as the role involves guiding prototypes through to production, so emphasising teamwork will be beneficial.
We think you need these skills to ace Data Scientist – PhD Computer Science, Recommender Systems, NLP, Machine Learning, Java
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your relevant experience in data science, particularly focusing on your work with recommender systems, NLP, and machine learning. Use specific examples to demonstrate your skills in Java programming and handling large datasets.
Craft a Compelling Cover Letter: In your cover letter, express your passion for research and technology. Mention how your background aligns with Elsevier's mission and the role's responsibilities. Be sure to include your experience in R&D environments and your ability to communicate complex ideas effectively.
Showcase Your Projects: If you have worked on relevant projects, especially those involving algorithms or data manipulation, summarise these in your application. Highlight any proof of concept prototypes you've built and the impact they had on previous projects.
Highlight Your Soft Skills: Beyond technical skills, emphasise your strong presentation skills and ability to collaborate with both experts and novices. This is crucial for a role that involves working with engineering teams and presenting findings.
How to prepare for a job interview at NLP PEOPLE
✨Showcase Your Research Skills
Be prepared to discuss your previous research projects in detail. Highlight your experience with algorithms, particularly in recommender systems and NLP, as this aligns closely with the role's requirements.
✨Demonstrate Technical Proficiency
Make sure you can talk confidently about your experience with Java and any big data technologies you've used. If you have worked with large graph or network data sets, be ready to share specific examples of how you handled them.
✨Prepare for Problem-Solving Questions
Expect to face technical questions that assess your problem-solving abilities. Practice explaining your thought process clearly, especially when discussing how you would approach developing and evaluating algorithms.
✨Communicate Effectively
Strong presentation skills are essential for this role. Be ready to explain complex concepts in a way that is accessible to both experts and novices. This will demonstrate your ability to collaborate effectively within teams.
