Data Scientist

Short Summary

Data Scientist with Cint. 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…

Key Details

• Position / opportunity: Data Scientist
• Organization: Cint
• Country / coverage: Remote
• Location: London, England, United Kingdom
• Work arrangement: Remote
• Opportunity type: Remote work opportunities
• Sector: Education
• Compensation: Not specified
• Duration: Not specified
• Start date: 2026-08-03
• Application deadline: Not specified

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. 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: 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. #LI-Remote #LI-JC1 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…

Responsibilities

• 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.

Requirements / Eligibility

• 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.

How To Apply

Use the Apply now button and follow the instructions on the application page.