Senior Data Scientist, Cint

• The ideal candidate will have a strong ability to independently research, develop, and maintain products that align Cint’s capabilities with market needs
• Must have a minimum 3-5 years of working experience in a Data Science capacity
• A Master's degree (or equivalent) in Statistics, Quantitative Sciences, Data Science, Operations Research, or other quantitative fields
• Ability to manipulate, analyze, and interpret large datasets independently
• Deep understanding of advanced statistical techniques and concepts (e.g., properties of distributions, hypothesis testing, parametric/non-parametric tests, survey design, sampling theory, experimental design, including multivariate testing, regression/predictive modeling, causal inference, and A/B testing)
• Strong knowledge of various machine learning techniques (clustering, regression, decision trees, etc.) and their real-world advantages and drawbacks
• Working knowledge of the application of statistical and modeling techniques
• Comfortable with researching and learning new methods, tools, and techniques
• Ability to independently and confidently manage projects from start to finish with minimal supervision
• Proficiency in Python (for statistical and ML package tools)
• Proficiency in SQL and working with large-scale databases
• Additional Information

Desirable

• As a Senior Data Scientist at Cint you will have the opportunity to collaborate closely with product and engineering teams to work on key Identity and Trust & Safety products and initiatives
• This role involves data mining and analytics, product and data validation, and the development of statistical and machine learning-based methodologies
• Lead the research, discovery, and development phases for new and existing products, primarily focusing on Identity and Trust & Safety
• Independently and confidently carry out project planning, development, and maintenance end to end with minimal supervision
• Analyze large, diverse datasets to extract impactful insights that can guide product strategy
• Collaborate with cross-functional teams to design, implement, and test new and existing products by developing and maintaining statistical and machine learning methods. Lead the full-cycle development of machine learning solutions, including model development, deployment, maintenance, and performance evaluation, ensuring seamless integration into production environments
• Continuously evaluate and validate both internal and external products to ensure Cint's continued success
• Communicate insights and recommendations effectively through visualizations and presentations that resonate with diverse audiences