At a Glance
- Tasks: Own analytics for participant lifecycle, using SQL and Python to enhance user experience.
- Company: Prolific, a leader in AI data infrastructure, shaping the future of AI development.
- Benefits: Competitive salary, remote work, and a mission-driven culture focused on innovation.
- Other info: Dynamic environment with opportunities for groundbreaking research and career growth.
- Why this job: Join us at the forefront of AI innovation, making a real impact with human data.
- Qualifications: Advanced SQL and Python skills, with experience in lifecycle analytics and experimentation.
The predicted salary is between 35000 - 42000 £ per year.
Prolific is not just another player in the AI space – we are the architects of the human data infrastructure that's reshaping the landscape of AI development. In a world where foundational AI technologies are increasingly commoditized, it's the quality and diversity of human-generated data that truly differentiates products and models.
The role involves maintaining a healthy and sustainable participant marketplace to meet the growing demand for high-quality human data. You will own analytics across the entire participant lifecycle, spanning acquisition, onboarding, activation, engagement, quality, retention, and reactivation. Working hands-on with SQL and Python, you will build the metrics, dashboards, and experimentation frameworks that help us understand behaviour and improve the participant experience. By partnering closely with Product, Operations, Growth, and Data Science, you will identify opportunities, structure experiments, and translate complex marketplace data into clear decisions that ensure participant health, marketplace liquidity, and long-term supply sustainability.
What you’ll bring to the role:
- Analytics Expertise: Advanced SQL and strong Python proficiency (e.g. pandas, experimentation analysis, automation), with a track record of building scalable reporting frameworks in modern BI tools (Metabase, Looker, Tableau). Comfortable owning problems end-to-end — from raw data to executive-ready insight.
- Lifecycle Analytics: Experience analysing user acquisition, onboarding, activation, engagement, retention, churn, and behavioural cohorts.
- Experimentation & Statistics: Experience designing and analysing A/B or operational experiments, with solid grounding in statistical concepts and causal thinking.
- Product Thinking: Ability to translate participant and marketplace challenges into measurable hypotheses, success metrics, and actionable recommendations.
- Commercial Acumen: Strong ability to connect operational metrics to revenue, margin, and financial performance — understanding not just what is happening, but why it matters commercially.
- Autonomy & Ownership: Comfortable operating with high autonomy in a fast-moving environment, setting priorities, challenging assumptions, and driving initiatives from problem definition through implementation.
- Stakeholder Management: Proven ability to partner across Product, Operations, Commercial, and Finance functions.
- Marketplace Understanding: Strong grasp of B2B and two-sided marketplace metrics and economics.
- Clear Communication: Ability to translate complex analysis into concise, decision-ready insights that shape strategy and execution.
Why Prolific is a great place to work:
We've built a unique platform that connects researchers and companies with a global pool of participants, enabling the collection of high-quality, ethically sourced human behavioural data and feedback. This data is the cornerstone of developing more accurate, nuanced, and aligned AI systems. We believe that the next leap in AI capabilities won't come solely from scaling existing models, but from integrating diverse human perspectives and behaviours into AI development. By providing this crucial human data infrastructure, Prolific is positioning itself at the forefront of the next wave of AI innovation – one that reflects the breadth and the best of humanity. Working for us will place you at the forefront of AI innovation, providing access to our unique human data platform and opportunities for groundbreaking research. Join us to enjoy a competitive salary, benefits, and remote working within our impactful, mission-driven culture.
Data Analyst - Supply employer: Doist
Brink's is an exceptional employer that fosters a collaborative and innovative work culture, empowering employees to drive global commercial strategies in the ATM lifecycle solutions sector. With a strong focus on professional development and growth opportunities, employees are encouraged to expand their skills while contributing to sustainable growth and operational excellence. Located in a dynamic environment, Brink's offers unique advantages such as a diverse team and the chance to build long-term partnerships with global customers, making it a rewarding place to advance your career.
StudySmarter Expert Advice🤫
We think this is how you could land Data Analyst - Supply
✨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 Doist!
✨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 Data Analyst - Supply at Doist.
✨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 Doist.
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When you find a suitable opening like Data Analyst - Supply at Doist, 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 Data Analyst - Supply
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 Doist, 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 Doist. 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 Doist
✨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 Doist!
✨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.
