Data Science Manager, Europe

Job Description

Auto req ID: 191714BR

Job Description

Lead the data science and advanced analytics initiatives for Perfect Store across ESSA, e.g. prediction of store potential, store segmetnation, assortment optimisation, etc.. The position exists to unlock competitive advantage in go-to-market and execution through cutting edge data science, advanced analytics and AI techniques, with a focus on Traditional Trade and Away from Home. The role holder will also leverage industry best practice to help to establish data science as a capability within the insight team and support the development of the data science, advanced analytics and AI agenda at PepsiCo

Accountabilities:

  • Lead Advanced Analytics projects that deliver business solutions through data science with a focus on go-to-maket and execution in traditional trade and away-from-home – working with different senior stakeholders and team leaders to leverage your expertise
  • Identify opportunities to leverage huge and varied datasets to find strategic advantage, while working with the data to create solutions
  • Consult with senior stakeholders to define business problems, and advise on how to apply data to solve those problems, e.g. sales opportunity prediction, assortment optimization, asset allocation etc.
  • Design and use algorithms and build models needed to automate generation of insights, identifying meaningful relationships across the massive sea of structured and unstructured data we have access to.
  • Elevate the role of Advanced Analytics across the business while developing our internal capability, the data science team and to derive insights from unstructured data through machine learning, collaborative filtering, location analytics, new AI tech etc.
  • Develop and continuously update a pipeline to enhance our existing tools to build greater simulation, forecasting and prediction capability, giving our business and our customers confidence that we can improve returns on current execution, asset deployment and activation plans.
  • Define the technology infrastructure that will take our data science, advanced analytics and AI capability to the next level.
  • Acting as an “evangelist” for data science within the business, building understanding of, and enthusiasm for, what can be achieved
  • Educate leadership on the opportunities associated with applying advanced analytics, data science and AI to the business, in particular in the areas of Perfect Store and go-to-market transformation
  • Partnering with other functions on leading analytics initiatives to define and identify solutions based on analytics and data-science

Qualifications/Requirements

  • PhD or Master’s degree or equivalent in Computer Science, Artificial intelligence, Machine Learning, Applied Statistics, Mathematics, Physics, Engineering or related field
  • ‘Best in class’ data science capabilities, with applied experience of machine-learning techniques including classifiers, regression, clustering, decisions trees, collaborative filtering, neural networks and ensemble techniques
  • Broad awareness of Data Science concepts including, Linear Regression, Logistic regression, Correlation variance, standard Dev, Dimensionality reduction, unsupervised learning, Parameter tuning, Cross Validation, boot strapping, Forecasting and Imputation.
  • Knowledge and experience of location intelligence and analytics a plus
  • A passion for the power of data and enthusiasm for turning this into ideas to present to the business
  • Experience in leading data science projects and data science teams
  • Understanding of the tech available to enable data science teams
  • Knowledge / experience of the consumer goods / F&B industry

Relocation Eligible: Not Applicable
Job Type: Pipeline


We are an equal opportunity employer and comply with the Equality Act 2010, we value diversity at our company; it is an essential part of our success. We do not discriminate on the basis of age, pregnancy or maternity, marital/civil partnerships, religion or belief, sex or sexual orientation, gender or gender reassignment, disability or race including; colour, nationality, ethnic or national origin.