At a Glance
- Tasks: Invent and implement methods to analyse unstructured evidence and drive impactful outcomes.
- Company: Innovative AI startup transforming data analysis for government and industry.
- Benefits: Competitive salary, flexible work environment, and opportunities for professional growth.
- Other info: Be an early hire and shape the future of our methodology and culture.
- Why this job: Join a pioneering team solving meaningful problems with cutting-edge technology.
- Qualifications: Strong background in statistical inference, causal inference, and machine learning.
The predicted salary is between 63000 - 77000 £ per year.
We’re building an analysis engine that helps organisations discover what is happeningand why.
It makes use of the evidence conventionaldata systems miss – from large internal text datasets to signals spread across many external sources.
Our architecture combines comparative statisticalinference and causal frameworks with machine learning and large languagemodels, ensuring stable interpretation andconsistent quality at scale.
We’re backed by a specialist AI venture fund, as well as receiving EU deep-tech funding.
Our team’s previous research has been cited over 35,000 times and has previously informed government and industry decision-making.
We’re now working with teams across government, pharma, and other large organisations, scaling our first deployments and building the scientific foundation forwhat comes next.
For too long, organisations have settled for a shallow, lagged view of the dynamics they care about.
We’re changing that, helping teams uncover the drivers that matter and build understanding thatimproves over time.
This is a hard, meaningful problem – come help us solve it.
What we’re looking for
We’re hiring an Applied Scientist to invent, validate and implement methods forworking out what drives outcomes from unstructured evidence.
You’ll explore thefrontier between statistical and causal inference and large language models – designingexperiments, prototyping pipelines, and collaborating with engineers tobring your best ideas into production quickly.
You’ll work directly with our CTO – a mathematician with deep experienceof turning complex data into real-world impact – and collaborate withenterprise clients to ensure our analysis is rigorous, scalable, andrelevant to decision-makers.
As one of our early hires, you’ll help shape Wholesum’smethodology, culture, and future.
About you
- You’re excited by the challenge of understanding cause and effect in messy, real-world data, and have a strong background spanning statistical inference, causal inference and machine learning.
- You’re excellent at pushing methodological boundaries and rapidly turning insights into well-designed Python pipelines.
- You spend a lot of your time innovating with LLMs, moving beyond basic tools, and enjoy working out where models fail and why.
- You have substantial experience evaluating and benchmarking statistical, ML and/or AI outputs.
- Experience producing analysis that informed real decisions under scrutiny and time pressure.
- Interest in human judgement, behaviour and decision-making.
- Understanding of common data collection and sampling methods.
- Experience building in early-stage or startup environments.
Applied Scientist employer: WholeSum Ltd
Wholesum is an exceptional employer that fosters a culture of innovation and collaboration, making it an ideal place for an Applied Scientist to thrive. With a focus on meaningful work that drives real-world impact, employees benefit from hands-on experience with cutting-edge technologies and the opportunity to collaborate closely with industry leaders. The supportive environment encourages professional growth and development, ensuring that every team member can contribute to transformative projects while enjoying a dynamic and engaging workplace.
StudySmarter Expert Advice🤫
We think this is how you could land Applied Scientist
✨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 WholeSum Ltd!
✨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 Applied Scientist at WholeSum Ltd.
✨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 WholeSum Ltd.
✨Apply Directly through Our Website
When you find a suitable opening like Applied Scientist at WholeSum Ltd, 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!
We think you need these skills to ace Applied Scientist
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 WholeSum Ltd, 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 WholeSum Ltd. 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 WholeSum Ltd
✨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 WholeSum Ltd!
✨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.
