ST
Seagate TechnologyData Science Intern
Data Science Intern leveraging AI and ML technologies for product development at Seagate. Hands - on experience with data analysis, model development, and actionable insights generation.
About the role
- 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
Analyst within Credit Risk Management team identifying credit segmentation opportunities using statistical methods. Collaborating with teams to enhance credit decision process and policies.
AM
AmoddexData Manager
Data Manager managing and analyzing company data at Amoddex, a consultancy for IT transformation projects. Ensuring data integrity and supporting strategic decision - making in a collaborative environment.
CO
Data Scientist at Capital One on the LLM Customization Team utilizing the latest in computing and machine learning technologies. Collaborating with data scientists and engineers to deliver AI powered products.
Lead Full Stack Data Scientist at Tilt, building the intelligence layer for data - based decisions. Driving data science strategy and analytics to enhance product and growth insights.
FC
Ford Motor CompanyData Science SME – AI/ML
Data Scientist focusing on Generative AI applications and engineering problem - solving at Ford. Collaborating with cross - functional teams to innovate and improve technology solutions in the automotive sector.
FC
Ford Motor CompanyData Scientist
AI Engineer/Data Scientist in Ford's Global Data Insights & Analytics team. Developing advanced AI/ML solutions and collaborating on cloud - native data products.
RI
RiachueloMid-level Data Scientist
Data Scientist transforming customer data into insights that guide strategic decisions for Riachuelo. Collaborating with teams to analyze and visualize data trends for business growth.
PF
Purpose FinancialVP, Credit Risk and Data Science
VP, Credit Risk & Data Science overseeing credit risk framework and portfolio management at Purpose Financial. Leading strategy and governance to enable profitable growth and risk mitigation.
CL
Compass LexeconData Scientist
Data Scientist joining a leading economic consultancy to implement data science solutions for business challenges and advance thought leadership in advanced analytics.