At a Glance
- Tasks: Lead AI and data science strategy, guiding teams from experimentation to production.
- Company: Join Elsevier, a leader in knowledge discovery and innovation.
- Benefits: Competitive salary, flexible working, and opportunities for professional growth.
- Other info: Dynamic role with opportunities to influence senior stakeholders and drive measurable outcomes.
- Why this job: Make a real impact in AI and data science while shaping the future of research.
- Qualifications: Proven experience in data science, leadership skills, and a passion for AI.
Elsevier in London seeks a Data Science Leader to define and lead AI and data science strategy across ML, NLP, search, and generative AI. You will guide teams through the full lifecycle from experimentation to production while aligning work to product goals and customer needs.
You will influence senior stakeholders, shape roadmaps, and drive measurable outcomes across the organisation by building high‑performing teams and delivering advanced AI systems for knowledge discovery at scale.
#J-18808-LjbffrSenior Data Science Leader - AI for Science & Discovery employer: Elsevier
At Elsevier, we pride ourselves on being an excellent employer, particularly for our Java Software Engineer role in Oxford. Our vibrant work culture fosters collaboration and innovation, while our commitment to employee growth is evident through continuous learning opportunities and flexible working arrangements that promote a healthy work-life balance. Join us to be part of a team that values your contributions and supports your professional journey in the exciting field of scientific knowledge sharing.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Data Science Leader - AI for Science & Discovery
✨Get Involved in Data Science Meetups
Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like Elsevier!
✨Show Off Your Projects
Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like Senior Data Science Leader - AI for Science & Discovery at Elsevier.
✨Leverage Professional Networks
Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like Elsevier.
✨Apply Directly through Our Website
When you find a suitable opening like Senior Data Science Leader - AI for Science & Discovery at Elsevier, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at Elsevier, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Elsevier. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at Elsevier
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Elsevier!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
