For Organization to remain competitive in the future, the business needs to continue its path to become data intelligent. The Information and Analytics team is responsible for building data, data science and analytics as a core capability to help the business become data intelligent and drive business and organization performance. The team will deliver advanced products at scale and work closely with the market teams to ensure that decisions in Organization are augmented with insight & recommendations wherever possible.
There are five major themes to the Information and Analytics strategy:
Deliver Intelligent systems at scale. Powering Business (cross functional) and Customer Development area through data and analytics. Building out the right applications to enable business teams to move faster, with more accurate and future looking decisions leveraging Big Data & Data Science
Winning disproportionately in Markets. We believe that the best way to move the needle for Organization in Analytics is to work with leading geographies to create analytics products that make a significant impact on our business
Drive Organization to assisted and predictive decision-making. The future is about assisted decision-making with machines (AI/Cognitive Computing/Machine Learning) unlocking the insights from vast deluge of consumer, customer & internal data, and presenting this in a way that is simple for our teams.
Make data a true asset. Better data and data science access for every part of Organization, across the 3-data framework (Connectivity, Growth, Continuous Improvement) and leading through the Enterprise Data Executive.
World-class Information: One Version of the Facts. Continued excellence in delivery of diagnostics and insights to focus attention when and where it matters with a focus on Big Bets, Strategic Initiatives and Leadership team reporting
This is an exciting new role in the Data Science and Analytics group in Information & Analytics, which is tasked to deliver maximum value from data to drive business and organization performance.
The Cross Functional data analytics product team helps build relevant assisted decision-making capabilities used by Category / Country Business Teams for driving P&L impact through superior insights underpinned by fully integrated sales, pricing, promotion, trade, media, competitive, and other related data.
The team is composed of product owners, data scientists, and data experts who can: quickly understand the business context + problem, apply advanced mathematics and/or statistics to large data sets; and operate in cloud based environments where data, models, and user interfaces reside in the same platforms-core technologies. Most critically, the team is tasked with building, delivering, and maintaining analytic capabilities that can be scaled and re-applied across divisions and markets.
Main Purpose of the Job:
Works with the product owner to fully understand the business problem and how to deliver relevant algorithms that lead to the right insights.
Builds, iterates, and refines analytic models to solve complex business problems and deliver predictions on potential future outcomes in a repeatable and relevant way across divisions and markets.
Supports adapting the algorithms and analytic models to evolving / changing business needs (change requests- CRs) on a going basis after they are put into production.
Specifically, this role will focus on leading the development of data-science and algorithmic solutions that power I&As portfolio of cross-functional (LiveWire) 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.
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 (LiveWire) product owner. They will have 2-3 Organization FTEs reporting into this role, and there may be third party contractors this role is accountable for (Fractal, or other potential local companies).
Ideal Candidate & Qualifications
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 analytics supplier (e.g. Nielsen, IRI, or other related companies)
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 (Nielsen, SAP, Retailer ePOS; 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