Principal Product Manager

Salary: £0 - £0

Location: London

United Kingdom

Apply by: 18/07/2018


Principal Product Manager

London

About the role

As Principal Product Manager for Recommendations Science, you will be a thought leader in the recommendations domain for Tesco, with ownership for the relevant platforms and algorithmic approaches within this portfolio across all markets that Tesco operates in. You will drive the algorithmic vision, product strategy, roadmap and execution for them, solving customer problems and delivering high value at scale. You will contribute to the wider strategy around personalisation and profiling.

You will be responsible for

Main Responsibilities 

Whilst specific responsibilities will be dependent upon the changing needs of the Tesco business, the following provides an overview of the role’s key responsibilities and measures;

  • Drive the global product vision, strategy and execution for Recommendations Science at Tesco, working closely with the Head of Data Science and the relevant Head of Product
  • Be a thought leader in the recommendations space and contribute to broader discussions, strategy and vision for personalisation and targeting at Tesco
  • Foster innovation and scientific discovery with a view to seeking out new applications for recommendations science across the wider business
  • Work closely with other product managers, product teams and business partners, across multiple business units and  domains (channels, markets, clients etc…) to solve customer and business problems, defining and agreeing outcomes and key results
  • Work closely with the Data Science team and relevant engineering teams to deliver maximum business value with least effort, always delivering value in slices
  • Represent the product organisation in key strategic decisions concerning relevant technology platform and suppliers
  • Maintain and establish new relationships with suppliers and business partners relating to recommendations science
  • Use leadership and negotiation skills to define and influence outcomes both within and outside of the organisation in order to achieve the best for Tesco customers, colleagues and partners
  • Determine and define the right mix of KPIs to judge the efficacy and drive material  improvements in recommendations capability, whilst collaborating on the right business KPIs that drive value to Tesco’s P&L
  • Make build vs buy decisions in collaboration with senior technology counterparts based on what is best for the product strategy
  • Inspire, mentor and coach other algorithmic (quantitative) Product Managers and Teams improving this discipline and capability at Tesco

 

You will need

Skills relevant for the job

Deep understanding of:

  • The Data Science Lifecycle (Business Understanding, Data Acquisition/Understanding, Modeling, Deployment, Acceptance)
  • Machine and Deep Learning approaches and when to apply them
  • Core recommendation approaches and their advantages and disadvantages (content based, user-based, collaborative filtering, factorisation techniques etc)
  • Offline evaluation methods and common performance metrics for recommendation systems (MAP, NDCG etc)
  • Text mining, text retrieval, indexes, ranking, relevance approaches
  • Cold-start recommendation problems
  • Processes for productionising recommendation engines at scale
  • Optimisation techniques at scale (A/B Testing, MVT etc…)
  • Excellent written and verbal communication skills
  • A methodical/ analytical approach and great problem-solving skills
  • Ability to evangelise a product domain to the wider business
  • Team player who could work collaboratively with other members of the team
  • Ownership, responsiveness and commitment towards assigned work
  • Strong decision making and prioritization skills, especially when multiple trade-offs are involved and faster decision are required
  • Empathy and good listening skills to understand the needs/pain points of your customers/ stakeholders
  • Supplier management and negotiation skills
  • Knowledge of Agile methodologies, writing effective user stories/acceptance criterions

Application process

Our office application process varies depending on the role and the level of experience needed.

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