At a Glance
- Tasks: Lead data science projects, develop AI/ML models, and drive impactful insights.
- Company: Join Multiverse, the UK's first EdTech unicorn transforming workforce skills.
- Benefits: 27 days holiday, health benefits, and opportunities for professional growth.
- Other info: Dynamic environment with a commitment to continuous learning and career development.
- Why this job: Make a real impact in the AI era while working with innovative tech.
- Qualifications: 5+ years in data science, strong Python skills, and experience with machine learning.
The predicted salary is between 36000 - 60000 € per year.
Multiverse is the upskilling platform for AI and Tech adoption. We have partnered with 1,500+ companies to deliver a new kind of learning that’s transforming today’s workforce. Our upskilling apprenticeships are designed for people of any age and career stage to build critical AI, data, and tech skills. Our learners have driven $2bn+ ROI for their employers, using the skills they’ve learned to improve productivity and measurable performance.
As a Senior Data Scientist, you will play a pivotal role in steering our Data Science team towards achieving strategic objectives. Your expertise will guide collaborative efforts in product and backend services alike, whilst collaborating with product experts, engineers and other stakeholders from across the organization. You’ll leverage your advanced analytical skills and understanding of AI and machine learning to drive impactful insights and foster innovative solutions. This dynamic role demands a balance of creativity and analytical rigor within a fast‑paced environment, ensuring quick learning and iteration based on user feedback.
What you’ll focus on:
- Translate complex stakeholder queries and hypotheses into actionable analyses, experiments and AI/ML model requirements.
- Develop a comprehensive understanding of our data lineage and sources, addressing and mitigating sampling and analytical biases.
- Oversee the productionisation of analyses and models, ensuring their seamless operation at scale by adhering to software engineering best practices.
- Drive targeted exploration of our data landscape, ideating and implementing innovative ways to use data for enhancing user engagement on our products.
- Build out our knowledge graph capability for underpinning AI/ML models and agentic workflows.
- Proactively monitor and refine analyses and models, optimizing effectiveness and efficiency while minimizing biases and operational challenges.
- Evaluate and validate scalable methodologies for data collection and processing, ensuring robust practices are in place.
- Communicate actionable insights to stakeholders at all levels, bridging the gap between technical concepts and business objectives.
What we’re looking for:
- 5+ years of data science/machine learning experience, with a proven track record in leading complex data projects.
- Extensive experience in deploying supervised/unsupervised machine learning algorithms and AI tools into production, delivering scalable and effective solutions.
- Strong proficiency in Python and key libraries commonly used in machine learning (e.g., NumPy, Pandas, Scikit‑Learn, PyTorch, Langchain).
- Advanced working knowledge of SQL.
- Experience with GitHub for version control.
- Demonstrated experience productionising ML models and analytic outputs within cloud environments (e.g., AWS, Azure).
- Understanding of best practices in data protection and information security.
- A tenacious, curious, and pragmatic approach to problem solving, focusing on creating usable, scalable outputs.
- Exceptional attention to detail and a strong analytical mindset.
- A growth‑oriented attitude and a passion for continuous learning and professional development.
- A commitment to Multiverse’s mission and values.
Non‑Required (But Desirable):
- Familiarity with the education/skills sector.
- Understanding of the semantic web, knowledge graphs and/or network analytics.
- Direct experience with CI/CD practices (e.g., GitHub Actions).
- Knowledge of infrastructure as code tools (e.g., Terraform).
- An advanced degree in a numerical, engineering or related discipline.
Benefits:
- Time off - 27 days holiday, plus 7 additional days off: 1 life event day, 2 volunteer days and 4 company‑wide wellbeing days and 8 bank holidays per year.
Data Scientist employer: Multiverse
Multiverse is an exceptional employer that champions a culture of continuous learning and innovation, making it an ideal place for Data Scientists to thrive. With generous benefits including 27 days of holiday plus additional wellbeing days, and a commitment to employee growth through hands-on experience in cutting-edge AI and tech projects, Multiverse empowers its team to make a meaningful impact in the workforce. Join us in our mission to transform the future of work while enjoying a collaborative and dynamic work environment in the heart of the UK's EdTech landscape.
StudySmarter Expert Advice🤫
We think this is how you could land Data Scientist
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with fellow data enthusiasts. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, analyses, and any cool AI/ML models you've built. This is your chance to demonstrate your expertise and creativity beyond just a CV.
✨Tip Number 3
Prepare for interviews by brushing up on common data science questions and case studies. Practice explaining your thought process clearly, as communication is key in bridging technical concepts with business needs.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you're genuinely interested in joining our mission at Multiverse.
We think you need these skills to ace Data Scientist
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the Data Scientist role. Highlight your experience with machine learning and data projects, and don’t forget to mention any relevant tools you’ve used like Python and SQL. We want to see how your skills align with our mission!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to tell us why you’re passionate about data science and how you can contribute to our goals at Multiverse. Be sure to connect your past experiences with the responsibilities outlined in the job description.
Showcase Your Projects:If you’ve worked on interesting data projects, make sure to showcase them! Whether it’s through a portfolio or links to GitHub, we love seeing practical examples of your work. This helps us understand your approach and creativity in problem-solving.
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it shows you’re keen on joining our team at Multiverse!
How to prepare for a job interview at Multiverse
✨Know Your Data Inside Out
Before the interview, dive deep into the data landscape of Multiverse. Familiarise yourself with their data sources and lineage. Be ready to discuss how you would address potential biases and sampling issues, as this shows your analytical rigor and understanding of the role.
✨Showcase Your Machine Learning Mastery
Prepare to talk about your experience with deploying machine learning models. Bring examples of past projects where you've successfully implemented supervised and unsupervised algorithms. Highlight any challenges you faced and how you overcame them, demonstrating your problem-solving skills.
✨Communicate Like a Pro
Since you'll be bridging the gap between technical concepts and business objectives, practice explaining complex ideas in simple terms. Think of ways to present your insights clearly and concisely, as effective communication is key to collaborating with stakeholders across the organisation.
✨Embrace Continuous Learning
Multiverse values a growth-oriented attitude, so be prepared to discuss how you stay updated with the latest trends in AI and data science. Share any recent courses, certifications, or projects that showcase your commitment to continuous professional development and your passion for the field.
