Must have

• SQL

• Python

• Polish (B2)

• English (C1)

Nice to have

• Machine learning

Requirements description

• Proven experience and Subject Matter Expertise in Supply Chain (ideally within the Retail/Grocery space)
• Advanced analytics and modelling experience
• Proven track record of informing business strategies and driving business change from actionable insight and data models or simulations
• Hands-on experience using SQL / BigQuery & Excel / Google Sheets
• Ability to translate an analysis or model into financial P&L impact to derive a business case
• Experience with BI tools such (Looker a plus)
• Able to plan complex work involving different crafts (e.g. Data Engineering, Data Science, Software Engineering) and different domains (e.g. Fulfilment, Ecommerce, Logistics)
• Confident in  communicating and influencing technical as well as non-technical senior management and key stakeholders, adapting the “data stories” and style to the audience
• Experience in mentoring and coaching more junior data analysts

It would be highly desirable if you also have the following (but not essential) :

• Curious to explore LLM use-cases to support decision making within Supply Chain / Analytics & Insight
• Experience with merchandising, fulfilment operations (customer fulfilment centres or store-based), Ecommerce or last mile home delivery operations
• Experience with Machine Learning
• Experience using Looker (building Explores and dashboards)
• Experience using Python (or other data oriented programming languages)

Offer description

• Standard benefits: life insurance, private health care [Luxmed], Multisport card, lunch vouchers, company share programs, and assistance for everyday worries and serious health problems.
• Learning opportunities: access to the Learnebly platform and LinkedIn Learning, English classes, and a book library,
• Parental support: additional +10 days maternity / +20 days paternity leave, funding for nurseries and kindergartens
• Hybrid model: 2 days/week in the office and flexibility to work from almost any location for up to 30 days a year.
• Office perks: centrally located offices with car and cycling parking, and home office equipment provided.
• Career growth: a clear career path with opportunities to rotate between projects, teams, domains and roles under the guidance of highly skilled senior colleagues
• High engineering culture: unique software engineering culture with a high level of test coverage and agile environment [read about our tech stack and engineering

practices across Ocado Technology]

• Speaker community: public speaking training and support for preparing presentations at conferences or meetups, including our own Ocado Technology Meetups
• Passions groups: running, cycling and more
• Annual celebrations: carnival, summer parties, family picnics, or kid’s days.

Your responsibilities

1. Strategic Contribution: Use Supply Chain domain knowledge and advanced analytics to influence the product strategy and roadmap, ensuring data-driven decision support is embedded within key initiatives
2. Analytical and Modeling Leadership: Design, develop, and implement modeling and optimisation techniques to address complex Supply Chain challenges, such as reducing supply chain costs, improving automated planning decisions, reducing substitution, optimising range, or minimising waste
3. Prototype and Testing: Explore opportunities for new models and tools, building prototypes and estimating business benefits. Conduct testing and measure impact on KPIs to refine models for deployment
4. Collaboration Across Teams: Work with Product Managers, Data Engineers, Data Scientists, and other stakeholders to integrate models and tools into the Ocado Smart Platform, ensuring user-friendly, scalable solutions for retail partners. Act as the representative of the broader Data Org within the Supply Chain Analytics & Insight Product Area
5. Mentorship and Knowledge Sharing: Mentor and guide junior analysts, sharing insights from both a domain and analytical perspective to uplift the team's capabilities
6. Explore AI for Supply Chain Decision-Making: Investigate and experiment with generative AI and other emerging technologies to enhance data-driven decision-making within the Supply Chain and Analytics domain

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