Cint is looking to solve media measurement and data solutions problems by working on products alongside Data Science and Analytics teams and collaborating with product and engineering teams.
Requirements
- 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, regression/predictive modeling, stochastic modeling/simulation, and more)
- Strong Knowledge of a variety of machine learning techniques (clustering, regression, tree-based models, etc.) and their real-world advantages/drawbacks.
- Working knowledge in application of statistical and modeling techniques.
- Proficiency in Python (as it relates to statistical analysis and implementing Machine Learning models)
- Ability to manipulate, analyze, and interpret large data sources independently.
- Experience with multivariate testing
- Ability to write and optimize SQL queries
Responsibilities
- Lead research, discovery and development phases for new and existing products/models relating to media measurement
- Independently and confidently carry out project planning, development and maintenance - end to end with minimal supervision
- Analyze a variety of large datasets to extract impactful insights that can drive product strategy
- Collaborate with cross-functional teams to align on design and implementation of models.
- Develop methodologies, validate, and maintain statistical and machine learning models.
- Ongoing evaluation and validation of both internal and external products to ensure Cint’s success.
- Communicate insights and recommendations through visualizations and presentations that will resonate with a wide range of audiences.
Other
- Master’s degree or equivalent in Statistics, Quantitative Sciences, Data Science, Operations Research or other quantitative fields.
- 5 years of experience in a data science capacity, preferably in market research, or advertising analytics.
- Self-starter that can independently and confidently carry out projects end to end with minimal supervision.
- Strong analytical skills with a focus on data validation and accuracy.
- Comfortable in researching and learning new methods, tools and techniques.
