
How your CV stacks up
Upload your CV to see how well it fits this job role
?%
Who We Are
Cint is a pioneer in research technology (ResTech). Our customers use the Cint platform to post questions and get answers from real people to build business strategies, confidently publish research, accurately measure the impact of digital advertising, and more. The Cint platform is built on a programmatic marketplace, which is the world’s largest, with nearly 300 million respondents in over 150 countries who consent to sharing their opinions, motivations, and behaviours.
We are feeding the world’s curiosity!
Job Description
As a Data Scientist at Cint, you will play a pivotal role in optimizing the Cint Exchange. Collaborating closely with product and engineering teams, you will deliver data-driven solutions to enhance the performance of existing products, inform the development of new offerings, and deepen our understanding of marketplace dynamics. This role involves advanced data mining and analytics, robust product and data validation, and the development of statistical and machine learning-based methodologies.
The ideal candidate will have a strong ability to independently research, develop, and maintain high-impact solutions that align Cint’s capabilities with market needs, directly influencing strategic decisions for the Exchange.
Responsibilities
- Lead the research, discovery, and full-cycle development of machine learning solutions, including model development, deployment, maintenance, and performance evaluation for the Cint Exchange.
- Develop a comprehensive, predictive understanding of marketplace dynamics, including price elasticity, supply/demand balance, and their underlying mechanics within the Cint Exchange.
- Independently carry out project planning, development, and maintenance with minimal supervision.
- Analyze large, diverse datasets to extract impactful insights that guide Exchange product and pricing strategy.
- Collaborate with cross-functional teams (Product, Engineering, Commercial, Operations, Finance) to design, implement, and test new and existing products.
- Apply and implement advanced statistical and machine learning methods to solve complex business problems.
- Conduct exploratory analyses into key metrics and lead the design and execution of A/B tests and other complex experiments to validate hypotheses.
- Create clear, effective deliverables that communicate complex insights and recommendations through compelling visualizations and presentations to both technical and non-technical stakeholders.
Reasons to use Rodeo
I’m in my final year doing Economics and I don’t know whether to apply for grad schemes now or do a masters first. What do you think?
Honest answer — it depends on where you want to end up. A lot of top grad schemes (Big 4, civil service, banking) don’t need a masters. Let’s look at the ones you’d be competitive for now, and we can decide if a masters actually adds anything.
Also worth knowing: most autumn 2026 applications are open now. Timing matters more than you think.
Start with a chat, not a search bar
Grad scheme, placement, apprenticeship? Not sure what you want yet — that's fine. Your agent talks it through with you and turns "I have no idea" into a shortlist.
Graduate Consultant — 2026 Scheme
Why you're a good match
StrongYour economics background and your summer at a regional bank line up with what PwC looks for on the consulting scheme. Applications close in four weeks.
See breakdownIt searches the market for you
Every day your agent scans the market matching roles against what actually matters to you, not just keywords on a CV.
Why you're a good match
You’ve got the grades and the economics background, and your bank internship is exactly the experience this scheme looks for. Apply soon — deadlines close within the month.
Experience fit
Your summer at the bank plus your econometrics coursework map directly to the day-one responsibilities on this scheme — client modelling, market briefings, and deal support.
Only hits
No noise. No "maybe this fits." Just roles with a clear explanation of why they're right — and where to focus when applying.
Qualifications
Qualifications Required:
- Minimum 3+ years of working experience in a Data Science capacity (adjust to 5+ if Senior).
- Master’s degree (or equivalent) in Statistics, Quantitative Sciences, Data Science, Operations Research, or a related quantitative field.
- Strong ability to manipulate, analyze, and interpret large, complex datasets independently.
- Deep understanding of advanced statistical techniques (e.g., hypothesis testing, parametric/non-parametric tests, survey design, experimental design, regression/predictive modeling, causal inference, and A/B testing).
- Solid knowledge of core machine learning techniques (e.g., clustering, regression, decision trees, neural networks) and their real-world tradeoffs.
- Proficiency in Python (for statistical and ML tools) and SQL (working with large-scale databases).
- Comfortable researching and adopting new methods, tools, and techniques.
Essential Qualities:
- Highly accountable self-starter and quick learner, motivated to deliver high-quality, impactful results.
- Strong data-driven mindset with the ability to translate abstract business requests into actionable analytical initiatives.
- Excellent written and verbal communication skills, with the ability to explain and defend technical findings to diverse audiences.
Nice to Have:


Get help with your application
Your very own career expert that helps elevate your application to the next level.
- Experience in marketplace dynamics, matching algorithms, or supply/demand optimization.
- Familiarity with financial datasets & commercial forecasting processes.
- Familiarity with web-analytics tools & optimizing user interfaces.
- Experience with survey exchange platforms or online market research products.
- Experience with Databricks, Spark, or PySpark for scalable data processing.
Additional Information
Our Values
Collaboration is our superpower
- We uncover rich perspectives across the world
- Success happens together
- We deliver across borders.
Innovation is in our blood
-
We’re pioneers in our industry
-
Our curiosity is insatiable
-
We bring the best ideas to life.
-
We do what we say
-
We’re accountable for our work and actions
-
Excellence comes as standard
-
We’re open, honest and kind, always.
-
We are caring
-
We learn from each other’s experiences
-
Stop and listen; every opinion matters
-
We embrace diversity, equity and inclusion.
More About Cint
We’re proud to be recognised in Newsweek’s 2025 Global Top 100 Most Loved Workplaces®, reflecting our commitment to a culture of trust, respect, and employee growth.
In June 2021, Cint acquired Berlin-based GapFish – the world’s largest ISO certified online panel community in the DACH region – and in January 2022, completed the acquisition of US-based Lucid – a programmatic research technology platform that provides access to first-party survey data in over 110 countries.
Cint Group AB (publ), listed on Nasdaq Stockholm, this growth has made Cint a strong global platform with teams across its many global offices, including Stockholm, London, New York, New Orleans, Singapore, Tokyo and Sydney. (www.cint.com)
Additionally, in a world of AI, we want our candidates to understand our approach to the use of AI during the interview and hiring process, so we'd appreciate you reading our AI usage guide.
“It took my CV and asked me questions relevant to understanding what kind of jobs to suggest for me. Suggestions were almost perfect. Jobs were exactly what I’ve been looking for.”
Jessica, London
Skills
Location