Responsibilities
- Apply and calibrate mathematical and econometric models to improve decision-making and generate clear explanatory insights.
- Develop, test, and deploy analytical algorithms and methods to support scalable, high-performance web analytics platforms.
- Build and validate analytical components for integration into modeling systems.
- Collaborate with software engineering teams to develop robust, production-ready analytical tools.
- Communicate technical approaches and findings clearly through documentation and presentations to both internal and external stakeholders.
Requirements
- Advanced degree (PhD or Master's) in Operations Research, Industrial Engineering, Applied Mathematics, Computer Science, or a closely related discipline.
- Minimum of four years of professional experience in data science or statistical analysis.
- Strong programming skills in Python, Spark, SQL, or comparable modern languages.
- Demonstrated experience applying machine learning frameworks and methodologies.
- Ability to write efficient, production-quality code using scientific computing libraries such as NumPy, SciPy, and Scikit-learn.
- Solid foundation in both Bayesian and Frequentist statistical inference.
- Clear and effective communication abilities in both spoken and written form.
- Highly organized with the ability to work independently on time-sensitive initiatives and deliver on schedule.
- Fast learner with strong logical reasoning, analytical capabilities, and a deep interest in technological innovation.
Nice to Have
- Familiarity with NumPyro is advantageous.
- Knowledge of cloud computing platforms such as AWS or Azure is beneficial.
- Experience with version-controlled code workflows, Docker, and CI/CD systems is a plus.
- Background working in rapid development cycles using agile methodologies like Scrum is preferred.
Responsibilities
- Use and fit different mathematical and econometric models for explanatory purposes that deliver better decisions, and create high-quality data visualizations for internal and external purposes.
- Research, design and implement analytic and mathematical approaches and algorithms to build scalable best of class web-based analytical solutions
- Design and test analytical modules for Nielsen modeling platforms
- Partner with our Software Engineering department to build best-of-class web-based analytical solutions
- Document and present methodology inside and outside the company
Required
- PhD or Masters degree in Operations Research, Industrial Engineering, Applied Mathematics, Computer Science, or Related field
- 4+ yrs experience in working in Data Science and/or Statistical analysis
- Expertise in Python, Spark, SQL or other modern programming languages
- Experience in using machine learning libraries and techniques
- Proficient in writing production grade code using scientific computing packages (e.g., NumPy, SciPy, Scikit-learn)
- Experience with Bayesian and Frequentist statistics
- Excellent oral and written communication skills
- Well-organized and capable of working independently on mission-critical projects while meeting deadlines
- Quick learner with a logical mindset and analytical thinking who is passionate about technology
Preferred
- Experience with NumPyro is a plus
- Familiarity with cloud providers (e.g. AWS, Azure) is a plus
- Experience in code management, docker, and CI/CD pipelines is a plus
- Experience in short-release life-cycle (agile processes including scrum) is a plus
