Senior Forecasting Analyst

Sainsbury's

Holborn, London

Ref: 19000B2J

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You will be working in one of the fastest growing and most dynamic areas of Sainsbury’s and supporting us in delivering an exceptional digital experience for all our customers through whatever food digital channel they should use. You’ll apply your expertise in understanding and organising data, managing data-intensive operational processes, and the application of statistical modelling techniques, to support the business in continuing to achieve rapid sales growth on a foundation of smooth-running, efficient operations. This will require understanding how customers interact with the various Food Digital channels and how our operations fulfil that demand. You will lead the maintenance and continuous enhancement of our forecasting and optimisation systems to leverage that understanding.

What You Need To Do

  • Interpret and investigate unstructured business requests in the light of technical understanding and the available data to formulate data analysis solutions with clearly articulated objectives
  • Working with peers build re-useable mathematical models to promote insight and understanding of the Food Digital business
  • Work with colleagues across the Sainsbury’s Data and Analysis Community to ensure the right data feeds are leveraged for online forecasting and optimisation
  • Take ownership of the final operational implementation of new data feeds and validated models for operational purposes in our continuously evolving forecasting and optimisation systems.
  • Maintain awareness of our evolving business needs from budget setting through to short-term optimisation across all Food Digital propositions, adapting our operational systems as required.
  • Where necessary, support the junior forecasting analyst with day-to-day operations
  • Undertake ad hoc analyses to interrogate questions that are not captured by our current models and systems, addressing emergent issues in our fast-paced business.

What You Need To Know

  • A strong analytical / quantitative degree (e.g. statistics, mathematics, physics, engineering, economics, geography, operational research)
  • Proven experience of analysing data, working with data systems and developing models in a corporate environment
  • Significant experience and proven aptitude for data wrangling and data engineering
  • Experience developing data systems with relational databases, and, ideally, other newer technologies
  • Demonstrated computer programming ability, including fluency in SQL, and R or Python, with appetite to broaden and gain experience with new tools
  • An advantage where candidates have prior knowledge of grocery, retail and online business.

What You Need To Show

  • You can consider broader business / divisional considerations in to your thinking – being cognisant of “operational reality”
  • How you can translate highly technical and analytical insights into actionable plans
  • You are comfortable working with stakeholders with varying perspectives across a large organisation (e.g. data governance, store teams) to progress data and systems engineering projects
  • Present and engage with multiple audiences (other technical teams and Operators, for example) with confidence and credibility. You’re able to both explain and engage and win over the hearts and minds of non-technical audiences
  • You can appreciate and understand the commercial relevance and significance of system improvements
  • Process large volumes of information, and identify the right priorities in which to invest time and energy in-order to maximise benefits and satisfy stakeholder needs
  • Build strong relationships with stakeholders, based on collaboration. Understand their perspectives and agenda
  • Demonstrate an understanding of implications outside your immediate remit to allow the Forecasting team to succeed, and focus on the right things
  • You’re organised and able to meet fixed deadlines

What Decisions I Can Make

  • Most appropriate way to approach key questions and how to resolve statistical issues
  • Accountability for Forecasting outputs, without peer / senior sign-off

Resources available to me

  • Advice and support from team and manager
  • Wider Forecasting team resource (4 people in total)
  • Budget for training / conference attendance and skill development where beneficial

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