Data Scientist supporting cross - functional AI/ML initiatives at Royal Caribbean Group. Designing, developing, and delivering analytical solutions with a focus on machine learning.
KA
Hybrid Lead Research Data Scientist – Fraud Detection, Market Research
Posted 3 months ago
About the role
- Lead Research Data Scientist developing models to detect fraud in online surveys. Joining Kantar's data division to innovate with data integrity, reproducibility, and advanced technologies.
Responsibilities
- Spearhead research-driven initiatives in detecting and preventing fraud and poor data quality within online market research surveys
- Develop and validate advanced models and systems for fraud detection
- Design, validate, and deploy novel machine learning models to detect fraudulent survey responses, including bots, duplicate entries, low-quality survey data and improbable or non-relevant responses
- Develop and maintain real-time scoring systems in production to assess respondent authenticity and engagement
- Conduct in-depth analysis of behavioural patterns, metadata, and response timing to uncover anomalies and suspicious activity
- Collaborate with survey operations, panel management, and research teams to embed fraud detection tools into survey workflows
- Patent novel algorithms & approaches to fraud detection within Market Research
- Provide thought leadership and mentorship to the team; promote best practices in ethical data handling, reproducible research, and experimental design
- Contribute to the wider Kantar data science ecosystem by presenting methodologies, publishing internal white papers, and facilitating knowledge exchange on fraud detection
- Stay abreast of academic and industry developments in fraud tactics, data validation, and respondent quality assurance
Requirements
- PhD in Data Science (or a highly relevant MSc plus real-world research experience), Statistics, Mathematical Modelling, Computer Science, or a related quantitative field
- Seniority and proven experience in data science, with at least 2 years focused on fraud detection, survey analytics, automated data quality solutions, or related research applications
- Strong proficiency in Python, R, SQL, and machine learning libraries (e.g., scikit-learn, XGBoost, TensorFlow, pyTorch)
- Experience with Kafka, ML Ops, and CI/CD pipelines is advantageous
- Experience with ML Ops & cloud platforms such as Azure ML and AWS is required
- Deep understanding of anomaly detection, behavioural modelling, and time-series analysis
- Deep research experience with NLP techniques for validating open-ended responses including applications Deep Learning for Gen AI / LLMs
- Experience with evaluation of LLMs such as LLM as a judge & human evaluated testing
- Strong communication skills, with the ability to translate technical findings into research insights and actionable recommendations
Benefits
- Competitive salary and performance-based bonuses
- Flexible working hours and hybrid work model
- Access to rich global survey datasets and cutting-edge tools, including state-of-the-art fraud detection models
- A collaborative, mission-driven team focused on data integrity, reproducibility, and innovation
- Opportunities for professional development, academic collaboration, and leadership growth
- Support for presenting at academic and industry conferences, and contributing to peer-reviewed publications where appropriate
Job title
Job type
Experience level
Salary
Not specified
Degree requirement
Tech skills
Location requirements
Health Data Scientist combining expertise in health communication, data analytics, and behavioral research. Joining a dynamic team to tackle global health challenges using data - driven methodologies.
Data Scientist helping Qliro develop payment solutions through machine - learning in credit and fraud domains. Collaborating in a modern data platform environment to enhance decision - making capabilities.
Data Scientist at Capital One using ML to revolutionize customer engagements through personalization. Collaborate with elite teams to build cutting - edge recommendation systems.
AI Agent Developer responsible for designing and building AI agents to operate within digital environments. Collaborating with teams to deliver innovative AI solutions and ensure functionality within complex systems.
AI Agent Developer designing and implementing autonomous intelligent agents using AI frameworks. Collaborating across teams to optimize agent capabilities and performance.
Data Science/Analyst Intern working with risk analytics and data science teams at Credibly. Engaging in projects that leverage advanced analytics and statistical techniques for business growth.
Senior Data Scientist leading data science initiatives impacting global operations across various business units. Collaborating with cross - functional teams to architect scalable machine learning solutions in cloud environments.
Lead Data Scientist building GenAI - driven products and ML solutions for S&P Global. Mentoring team members and delivering high - impact projects in a global environment.
Data Scientist in Digital Transformation team at Lavazza implementing machine learning models and managing model lifecycle within Agile squads. Focusing on solving real business problems.