Senior Data Scientist

Cint is a pioneer in research technology (ResTech). Our customers use the Cint platform to post questions and get answers from real people to build business strategies, confidently publish research, accurately measure the impact of digital advertising, and more. The Cint platform is built on a programmatic marketplace, which is the world’s largest, with nearly 300 million respondents in over 150 countries who consent to sharing their opinions, motivations, and behaviours.

We are feeding the world’s curiosity!

Job Description

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. The ideal candidate will have a strong ability to independently research, develop, and maintain products that align Cint’s capabilities with market needs.

Responsibilities

• 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.

Qualifications

Required:

• Must have a minimum 3-5 years of working experience in aData Sciencecapacity.
• 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 inPython(for statistical and ML package tools).
• Proficiency inSQLand working with large-scale databases.

Additional Information

Nice to Have:

• Experience in Fraud Detection and Prevention methodologies.
• Experience working with Identity vendors.
• Knowledge of Identity graph methodologies.
• Experience with Databricks and using it for scalable data processing and machine learning workflows.
• Experience working with big data technologies (e.g. Spark, PySpark).

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