At a Glance
- Tasks: Design and prototype AI/ML methods to enhance data quality and support AI evaluation workflows.
- Company: Join a forward-thinking tech company focused on real-world impact through AI.
- Benefits: Competitive salary, flexible working hours, and opportunities for professional growth.
- Other info: Dynamic role with a focus on practical solutions and innovative methodologies.
- Why this job: Make a tangible difference in AI systems while collaborating with diverse teams.
- Qualifications: PhD or MSc in relevant fields and 3+ years of applied ML experience.
The predicted salary is between 80000 - 98000 £ per year.
Requirements
- Ideal for someone with deep scientific judgement, strong applied ML skills, and a practical bias toward methods that work in real customer and product contexts.
- PhD or MSc in Computer Science, Mathematics, Statistics, Machine Learning, or a related field.
- 3+ years of applied ML, AI research, or data science experience with demonstrated real-world impact.
- Experience with human-in-the-loop AI systems, including RLHF, annotation pipelines, data quality modelling, judgement aggregation, benchmarks, or AI evaluation.
- Fluency with modern LLM and agentic techniques, such as Retrieval-Augmented Generation (RAG), LLM-as-judge, multi-agent workflows, synthetic data generation, and automated quality review.
- Strong Python skills and the ability to quickly build, test, and iterate on working prototypes.
- Good judgement on when to use simple statistical methods, classical ML, LLMs, or agentic approaches.
- Ability to translate ambiguous product or customer problems into clear hypotheses, experiments, metrics, and reusable methodologies.
- Strong cross-functional communication and experience partnering with product and engineering teams.
What the job involves
- As an Applied Scientist, you will design and prototype AI/ML methods that improve data quality, scale human judgement, and support robust AI evaluation workflows.
- You will work on applied problems such as quality modelling, judgement aggregation, evaluation design, LLM-assisted review, and reliability testing for AI systems.
- This is not a pure research role or a production ML engineering role. You will turn ambiguous problems into clear methodologies, benchmarks, models, and prototypes that product and engineering teams can adopt.
- Prototype AI/ML methods to improve human data quality, judgement aggregation, and AI evaluation workflows.
- Design experiments, benchmarks, and reliability tests to measure whether new methods improve quality, efficiency, or customer outcomes.
- Apply classical ML, statistics, LLMs, and agentic techniques where they create practical value.
- Use modern AI tools to accelerate prototyping, experimentation, and iteration.
- Partner closely with product and engineering to translate scientific methods into scalable platform capabilities.
- Communicate technical assumptions, trade-offs, and recommendations clearly across technical and non-technical teams.
Lead Applied Scientist (12 Month Fixed Term Contract) in London employer: Prolific
Join a forward-thinking company that values innovation and collaboration, where as a Lead Applied Scientist, you will have the opportunity to work on impactful AI/ML projects in a dynamic environment. Our culture fosters continuous learning and growth, providing you with access to cutting-edge tools and resources, while our commitment to employee well-being ensures a supportive workplace. Located in a vibrant area, we offer unique advantages such as flexible working arrangements and a strong emphasis on work-life balance, making us an excellent employer for those seeking meaningful and rewarding careers.
StudySmarter Expert Advice🤫
We think this is how you could land Lead Applied Scientist (12 Month Fixed Term Contract) in London
✨Tap into Online Data Science Communities
Join online communities focused on data science like Kaggle, LinkedIn groups, or Reddit threads. These are goldmines for temporary gigs, as you can network with professionals and potentially hear about opportunities at companies like Prolific before they're even advertised!
✨Show Off Your Skills With Projects
Got some cool data science projects? Showcase them on platforms like GitHub or create a personal portfolio website. This visibility is crucial for landing temporary roles—let recruiters see your actual skills in action, which can set you apart from the crowd.
✨Check Out Specialist Job Boards
For temp roles, hit up job boards dedicated to tech and data science, like Stack Overflow Jobs or DataJobs. These platforms often feature openings that you won’t find on general job sites, including contracts with companies like Prolific.
✨Leverage University Resources
If you're currently at uni or recently graduated, tap into your school's career services. They often have connections with companies looking for temporary data science interns or contract workers, and they might even host job fairs with employers like Prolific.
We think you need these skills to ace Lead Applied Scientist (12 Month Fixed Term Contract) in London
Some tips for your application 🫡
Highlight Your Data Projects:When applying for a temporary data science role at Prolific, make sure to showcase any relevant projects you've worked on. Whether it's a personal project, an academic undertaking, or contributions to an open-source initiative, detailing these experiences can really set you apart and demonstrate your practical skills.
Emphasise Your Analytical Skills:In your CV and cover letter, focus on the specific analytical skills that are key to data science. Mention any experience with statistical tools, programming languages like Python or R, and data visualisation software. Don't forget to include any certifications that may bolster your expertise!
Show Your Flexibility:Since this is a temporary role, it's important to convey your adaptability and willingness to learn. In your cover letter to Prolific, emphasise how quickly you can get up to speed with new tools or projects. Highlight any previous experiences where you've had to adjust to new environments or challenges.
Craft a Unique Data-Driven Cover Letter:Instead of the usual generic cover letter, spice it up with some data! Maybe you’ve improved a process by 20% in a past role or cleaned a dataset with over a million entries. Use these stats to your advantage to grab Prolific’s attention and show the tangible impact of your work.
How to prepare for a job interview at Prolific
✨Showcase Your Analytical Skills
For a data science gig, it's crucial to demonstrate your analytical abilities. Be ready to discuss previous projects and the methodologies you used. Think about how you can quantify your impact—did your analysis improve efficiency or save costs? These are the stories that will stick with interviewers at Prolific.
✨Brush Up on Technical Skills
You might face technical questions on tools relevant to data science, like Python, R, or SQL. Prepare to solve a problem live—perhaps they'll ask you to write a simple query or code snippet. It’s cool to talk about them, but we need to show we can do it in practice, especially in a temporary role where quick results matter.
✨Highlight Your Adaptability
Since this is a temporary position, emphasise your ability to learn quickly and adapt to new tools or workflows. Share examples of how you've thrived in fast-paced environments before, and how you can hit the ground running at Prolific.
✨Prepare a Portfolio of Your Work
Bring your portfolio to the table—showcase projects where you've leveraged data science techniques to solve problems. Whether it’s a GitHub repository or a set of case studies, having tangible examples of your work will help you stand out and show what you bring to the team at Prolific.
