Senior Data Scientist

Company Description

Cint is a pioneer in the 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 behaviors.

We are feeding the world’s curiosity!

Job Description

As a Senior Data Scientist, you will sit at the intersection of product, engineering, and advanced analytics.

You will architect the statistical methodologies and machine learning codebases that power our Media Measurement products, directly translating raw global data into strategic insights that drive the ResTech industry forward.

What You Will Deliver:

• Lead the research, discovery, and end to end development phases for new and existing machine learning models relating to media measurement.

• Extract, manipulate, and analyze massive datasets to uncover insights that shape and direct our product roadmap.

• Partner closely with engineering and product teams to align on the technical design, deployment, and ongoing validation of scalable machine learning models.

• Transform complex statistical outputs into compelling visualizations and presentations that resonate with diverse business and technical audiences.

Key Responsibilities:

• Lead research, discovery, and development phases for new and existing statistical models relating to media measurement.

• Plan, develop, and maintain data science projects from end to end with minimal supervision.

• Analyze large, complex datasets to extract insights that inform product strategy.

• Collaborate with cross-functional engineering and product teams on model design and implementation.

• Develop, validate, and maintain statistical and machine learning models.

• Conduct ongoing evaluation and validation of internal and external product methodologies.

• Communicate findings and statistical recommendations through clear visualizations and presentations for technical and non-technical stakeholders.

Qualifications

• Master's degree or equivalent in Statistics, Quantitative Sciences, Data Science, Operations Research, or another quantitative field.

• 5 years of experience in a data science capacity, preferably in market research or advertising analytics.

• Ability to manipulate, analyze, and interpret large data sources independently.

• Deep understanding of advanced statistical techniques and concepts, including:

  • Properties of Distributions

  • Hypothesis Testing

  • Parametric and Non-Parametric Tests

  • Survey Design

  • Sampling Theory

  • Experimental Design, Regression or Predictive Modeling

  • Stochastic Modeling or Simulation.

• Strong knowledge of machine learning techniques, such as:

  • Clustering

  • Regression and their real-world trade-offs

  • Tree-based models and their real-world trade-offs

• Working knowledge of the application of statistical and modeling techniques.

• Strong analytical skills with a focus on data validation and accuracy.

• Ability to independently research and learn new methods, tools, and techniques.

• Self-starter capable of carrying out projects from start to finish with minimal supervision.

• Proficient in Python for statistical analysis and machine learning model implementation.

Nice to Have:

• Experience in media measurement and digital attribution.

• Experience with multivariate testing.

• Experience with predictive modeling.

• Experience modeling and quantifying outcomes by linking attitudinal survey data to behavioral purchase data.

• Experience in online survey methodologies.

• Ability to write and optimize SQL queries.

• Experience working with big data technologies, such as Spark.