Senior AI/ML scientist in Computational Toxicology driving advanced AI/ML solutions for safer drug discovery and regulatory methodologies.
KA
Hybrid Lead Research Data Scientist – Fraud Detection, Market Research
Posted 6 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
AI Reliability Data Scientist focused on predictive models and industrial data analysis for advanced manufacturing projects in Mexico.
Data Scientist/Senior Data Scientist overseeing evaluation of quantitative risk management practices at Federal Reserve Bank. Engaging in reviews, analyses, and internal consulting within the organization.
Lead Data Scientist at Federal Reserve Bank of Atlanta. Conducting quantitative risk management analysis and participating in regulatory reviews of large BHCs.
Seeking a Data Scientist/Machine Learning Semi Senior to develop data - based solutions in Buenos Aires. Must have strong Python skills and experience in Machine Learning.
Data Scientist/Developer at SEB transforming complex financial data into predictive insights through data modeling and simulations. Strong Python and finance skills required in a hybrid work environment.
Senior Data Scientist leveraging computer vision and machine learning to support Quality Control at Walmart. Collaborating with engineering and business to deliver scalable data solutions.
Senior Data Scientist addressing complex ML and AI challenges at JLL. Collaborating in a hybrid environment with a focus on real estate technology in Tel Aviv.
Applied Data Scientist designing and implementing AI - driven pipelines for Binance's blockchain products. Collaborating on complex systems to enhance market understanding and trading intelligence.
Data Science Team Lead at OREDATA, leading teams to resolve data science challenges in a hybrid environment. Joining a digital transformation firm with a strong collaborative culture.