Senior Health Data Scientist leading complex data extraction and modeling for healthcare solutions at Inovalon. Collaborating with multidisciplinary teams to deliver data - driven insights.
KA
Hybrid Lead Research Data Scientist – Fraud Detection, Market Research
Posted 6 months ago
About the role
- Lead Research Data Scientist combating fraud and enhancing data quality in online market research. Spearheading research-driven initiatives using machine learning and behavioral analytics for Kantar.
Responsibilities
- Spearhead our research-driven initiatives in detecting and preventing fraud and poor data quality within online market research surveys
- Develop and validate advanced models and systems that uphold the integrity of our data and the robustness of our insights
- 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
Data Scientist developing machine learning solutions and delivering insights for operational decisions. Collaborating with stakeholders to apply analytical techniques and improve business outcomes.
Data Scientist responsible for modeling and analyzing credit risk at CAIXA Consórcio. Utilizing data - driven insights to support strategic decision - making in credit operations.
Data Scientist optimizing payments ecosystem for Preply, enhancing user experience through data - driven insights. Collaborating with teams to improve payment processes and fraud management.
Staff Data Scientist at Preply developing data strategies for product domains. Collaborating with executives to drive long - term strategy and experimentation frameworks.
BA
Data Manager leading data strategy and governance for Global Payments Solutions at Bank of America. Managing data architecture aligning with business and regulatory needs while overseeing complex data ecosystems.
Data Scientist developing and implementing LLM - based agents and leveraging AI techniques to improve client value. Collaborating on project challenges in a dynamic, start - up environment at Gartner.
Data Scientist in AI SaaS integrating 100+ systems for a European unicorn - in - the - making. Ensure scalability, security, and performance in a high - growth environment.
Data Science Intern working on AI - driven recipe and hardware optimization problems in semiconductor processes. Developing machine learning models and collaborating with engineering teams for innovative solutions.
Senior Data Scientist at LexisNexis developing AI - driven solutions for legal analytics. Collaborating with teams to implement machine learning models and monitor performance metrics.