Lead Data Scientist - Statistical Expertise

Key Skills

Data science techniques, Design, Effective communication skills, Git, Leadership Skill, Machine learning techniques, Python Programming, R Programming, SAS, Scikit-learn, SciPy, SPARK Programming, SQL

Job Description

We research and develop causal inference model that measures accurately and precisely the causal

effects of advertising, promotion, distribution, assortment, and other factors to inform clients of the

historical effectiveness of their marketing tactics and exogenous factors on outcomes. To improve the

operational efficiency of causal inference solutions, we develop automated and scalable supervised

and unsupervised learning methods that yield accurate outcome predictions and labeling.

Key Responsibilities

• Research, design, develop, implement, and test econometric, statistical, causal inference, and
• machine learning models.
• Create various prototypes for research and development purposes.
• Design, write and test modules for Nielsen analytics platforms using Python, SQL, Spark, and
• AWS products.
• Utilize advanced computational/statistics libraries including Spark MLlib, Scikit-learn, SciPy,
• StatsModel, SAS and R
• Document and present econometric, statistical, and causal inference methods to within
• company associates.
• Work with Product on setting the direction for new analytics research and product
• development for engaged track(s).
• Partner with Product organization on resolving issues that users face.
• Provide guidance to junior data scientists.

Key Skills

• PhD level coursework in Statistics, Econometrics, Applied Mathematics, Biostatistics,
• Chemometrics, Computer Science subfield of Machine Learning, Industrial Engineering,
• Operations Research, Psychometrics, Physics, or other discipline that is concerned with
• developing and studying methods for collecting, analyzing, interpreting and presenting
• empirical data.
• Expertise in coding and testing of analytical modules using Python, SQL, Spark, and AWS.
• Expertise in at least one statistical software or machine learning package, such as Scikit-learn
• and StatsModels.
• Experience with Git or other version control tools.
• Well-organized and capable of handling multiple mission-critical projects simultaneously while
• meeting deadlines.
• Excellent oral and written communication skills
• Systematic thinking skills to predict edge cases and identify risks during code development.
• Critical thinking skills to evaluate results in order to make decisions.
• Abilities to solve problems independently and within a team.
• Work with cross-functional team to resolve any hurdles in the projects.
• Experience managing or mentoring data scientists.

Requirements

• Graduate degree in Statistics, Economics, Applied Mathematics, Computer Science,
• Engineering, or other Quantitative Field of Study.
• 7+ years of work experience in delivering analytics software solutions in a production
• 7+ years of work experience in quantitative marketing analysis, with an emphasis on
• statistical, econometric and predictive analytic research that drives analytic product Innovation
• and implementation.

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