Senior Manager - Data Science - CPG/Retail

Specifically, this role will focus on leading the development of data-science and algorithmic solutions that power I&A's portfolio of cross-functional products. The role will integrate design inputs provided by cluster and market I&A business analysts and business topic SMEs (e.g. market share decomposition); and prioritize the most critical features into their models - ensuring a healthy balance between global scale and local relevancy. Furthermore, the role owns the future CR roadmap post product launch.

Key accountabilities:

- Build data-science and algorithmic solutions to address business problems requiring descriptive, diagnostic, predictive, and/or prescriptive analytics for addressing business questions linked to Cross functional processes (S&OP, Innovation, NRM, integrated business planning, and other related processes)

- Innovate new data and analytic methodologies by partnering closely with in-market data scientists who are engaged - linked closely with Category / Country business teams (CCBTs)

- Develop the 12-month roadmap of data-science and algorithmic enhancements

- The position will be an individual contributor and manager role working closely with the Cross functional product owner. They will have 2-3 FTEs reporting into this role, and there may be third party contractors this role is accountable for (Fractal, or other potential local companies).

Relevant Experience:

- B.S. or M.S. in a relevant technical field (Operations Research, Computer Science, Statistics, Business Analytics, Econometrics, or Mathematics). Overall experience of 8-10+ years preferred

- 3-5 years of experience working in a fast-moving consumer goods company and/or data - analytic supplier

- Strong track record in solving analytical problems using quantitative and statistical approaches

- Expert knowledge in statistics (Regression, Clustering, Random Forrest, Decision Trees, Optimization, Time Series, Probability, and other related advanced methodologies)

- Expert knowledge of an analysis tool such as Angoss, KNIME, Spotfire, Microsoft PowerBI, and Tableau

- Expert knowledge working with and coding in R, R Shiny, and Microsoft Azure Machine Learning

- Ability to manipulate and analyse complex, high-volume, high-dimensionality data from varying sources both structured and non-structured data.

- Experienced knowledge working with large data sets, experience working with distributed computing tools a plus (Map/Reduce, Hadoop, Hive)

- Experienced knowledge working in Microsoft Azure and applying Cortana to develop scaled analytic models in the cloud

- Experienced knowledge with relational and columnar databases - SQL is a plus

- Passion for empirical research and for answering hard questions with data

- Ability to apply an agile analytic approach that allows for results at varying levels of precision

- Ability to communicate complex quantitative insights in a precise, and actionable manner