Remote Senior Data Scientist

Summary

The job is a Senior Data Scientist position at Pixalate focusing on Ad Tech Fraud Detection & Prevention with AI/ML and Privacy Expertise. The role requires minimum experience, is full-time, and remote. The team spans globally, and the work involves analyzing large datasets, developing AI/ML algorithms, and ensuring compliance with global privacy laws.

Requirements

• BS in Computer Science, Electrical Engineering, Math, Physics, or other quantitative fields
• 4+ years of professional experience in data science, solving complex problems with a focus on AI/ML techniques and privacy expertise
• Experience in implementing AI/ML algorithms, including deep learning and reinforcement learning models, while ensuring compliance with privacy and data protection laws
• Strong critical thinking and ability to generate intuitive conclusions from complex datasets
• Excellent verbal and written communication skills, with a high attention to detail
• Proficiency in SQL and Python (experience with R is a plus)
• Solid understanding of machine learning algorithms, basic probability, and statistics
• Familiarity with AI/ML tools and frameworks (e.g., OpenAI, ChatGPT, TensorFlow, PyTorch, Keras)
• Familiarity with online advertising, advertising fraud, and global privacy and data protection laws, with a focus on European privacy and data protection laws and regulations

Responsibilities

Analyze large datasets, develop AI/ML algorithms, and derive insights to address complex business problems in fraud detection/prevention and advertising data analytics while ensuring compliance with global privacy and data protection laws

Preferred Qualifications

• MS or PhD degree in Computer Science, Electrical Engineering, Math, Statistics, or other quantitative fields with a focus on AI/ML and privacy expertise
• Familiarity with Amazon AWS, UNIX CLI, and programming in Scala, Java, and/or C/C++ (a plus)
• Experience providing thought leadership in privacy and data protection, particularly in the context of the European regulatory landscape and beyond
• Proven track record of integrating privacy-by-design principles into data science projects and products
• Knowledge of de-identification, anonymization, and pseudonymization techniques for data processing and analysis
• Familiarity with privacy-enhancing technologies (PETs) and their applications in AI/ML projects
• Experience working with data protection authorities and managing data protection impact assessments (DPIAs) in a data-driven organization
• Strong understanding of GDPR, ePrivacy, and other relevant privacy and data protection legislation, as well as global privacy frameworks and best practices

Benefits

• Generous benefits package including 25 days holiday plus Bank holidays
• Defined contribution Pension scheme
• Monthly internet reimbursement
• Casual, remote work environment
• Hybrid, flexible hours
• Opportunity for advancement
• Fun annual team events
• Being part of a high performing team that wants to win and have fun doing it
• Extremely competitive compensation