Senior Data Analyst - Ocado Solutions

Ocado Group
Hatfield
2 months ago
Applications closed

Related Jobs

View all jobs

Senior Data Analyst

Senior Data Analyst

Senior Data Architect

Senior Data Governance Analyst

Senior Data Engineer

Commercial Data Analyst

Senior Data Analyst | Ocado Solutions | Hatfield (Hybrid, 2 days in the office)

"We are on a mission: To transform the future of grocery retail through sustained technology innovation."

At Ocado Group, we are redefining grocery retail using cutting-edge technologies such as robotics, AI, IoT, and cloud computing. By designing all our software and systems in-house, we consistently innovate to create game-changing solutions-from dynamic e-commerce platforms to fully automated warehouses.

This role sits within Ocado's Solutions division, supporting our Ocado Smart Platform (OSP) Partners globally. Delivering consistent and impactful support is essential to fostering long-term relationships and ensuring commercial success.

The Solutions Analytics team's mission is to "Provide the insight, advice, and services to help our partners and prospects succeed and grow with OSP."
About the Role
As a Senior Data Analyst, you will extract and interpret data to identify opportunities for efficiency and growth within our partners' delivery operations. Your insights will influence multi-million-pound decisions, enhance customer experiences, and contribute to Ocado's mission of transforming grocery retail.

In addition to working with vast datasets and advanced tools, you'll lead impactful projects, mentor junior analysts, and shape analytics solutions that drive global partner success.
Key Responsibilities

  • Insight Generation:Extract, analyse, and interpret data to identify trends and opportunities for OSP Partners, driving growth and efficiency.
  • Strategic Projects:Lead analytical contributions to cross-functional projects that deliver significant business outcomes.
  • Collaboration:Partner with technology, operations, and external stakeholders to optimise OSP's impact
  • Visualisation & Communication:Create compelling dashboards and reports, presenting insights in actionable, user-friendly formats.
  • Mentorship:Guide junior analysts, fostering a collaborative and innovative team environment
  • Continuous Improvement:Close data gaps, enhance platform features, and contribute to analytics best practices.
  • Sustainability Impact:Support initiatives to optimise operations, reducing waste and carbon emissions.

What We Are Looking For
Essential Skills and Experience

  • Proven Analytical Expertise:4 years of experience in data analytics, working with Big Data to deliver actionable insights.
  • Technical Skills:Proficiency in SQL, Excel/Google Sheets, and visualisation tools (e.g., Looker, Tableau, Data Studio).
  • GIS Proficiency:Experience with GIS software to drive location-based insights.
  • Problem-Solving Mindset:Strong capability to analyse and resolve complex issues.
  • Communication Skills:Ability to present insights to technical and non-technical audiences, including senior stakeholders.
  • Global Perspective:Experience working in diverse, cross-cultural environments.
  • Leadership:Ability to mentor and support junior team members while leading projects autonomously.

Desirable Skills

  • Proficiency in Python and Google Colab for advanced data processing.
  • Familiarity with AI-driven analytics and predictive modeling.
  • Additional language skills (e.g., Spanish, French, Japanese, Korean).
  • Experience in online grocery, retail, or logistics analytics.
  • Knowledge of data governance, security, and privacy best practices.

What We Offer
We value and support our colleagues with a wide range of benefits designed to promote wellbeing, work-life balance, and professional growth:

  • Hybrid working(2 days in the office).
  • 30 days of remote work from anywhere globally.
  • Fully remote working during August.
  • 25 days annual leave(rising to 27 after 5 years), plus the option to purchase additional holidays.
  • Pension schemewith employer contribution matching up to 7%.
  • Opportunity to participate inShare SaveandBuy as You Earn schemes.
  • Interest-freetrain ticket loan.
  • Cycle to Work Scheme.
  • Private medical insurance.
  • 22 weeks paid maternity leaveand6 weeks paid paternity leave(subject to service requirements).
  • Income protection(up to 50% of salary for 3 years) andlife assurance(3x annual salary).
  • 15% discount on Ocado.comand free delivery for employees.
  • Free shuttle bus to and from Hatfield train station.

#LI-HYBRID

#LI-OT

#LI-OS

#LI-JT1YmJnZW5lcmljLjI5MTY2LjEyMjcxQG9jYWRvcHJvZC5hcGxpdHJhay5jb20.gif

Get the latest insights and jobs direct. Sign up for our newsletter.

By subscribing you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Tips for Staying Inspired: How Data Science Pros Fuel Creativity and Innovation

Data science sits at the dynamic intersection of statistics, computer science, and domain expertise, driving powerful innovations in industries ranging from healthcare to finance, and from retail to robotics. Yet, the daily reality for many data scientists can be a far cry from starry-eyed talk of AI and machine learning transformations. Instead, it often involves endless data wrangling, model tuning, and scrutiny over metrics. Maintaining a sense of creativity in this environment can be an uphill battle. So, how do successful data scientists continue to dream big and innovate, even when dealing with the nitty-gritty of data pipelines, debugging code, or explaining results to stakeholders? Below, we outline ten practical strategies to help data analysts, machine learning engineers, and research scientists stay inspired and push their ideas further. Whether you’re just starting out or looking to reinvigorate a long-standing career, these pointers can help you find fresh sparks of motivation.

Top 10 Data Science Career Myths Debunked: Key Facts for Aspiring Professionals

Data science has become one of the most sought-after fields in the tech world, promising attractive salaries, cutting-edge projects, and the opportunity to shape decision-making in virtually every industry. From e-commerce recommendation engines to AI-powered medical diagnostics, data scientists are the force behind innovations that drive productivity and improve people’s lives. Yet, despite the demand and glamour often associated with this discipline, data science is also shrouded in misconceptions. Some believe you need a PhD in mathematics or statistics; others assume data science is exclusively about machine learning or coding. At DataScience-Jobs.co.uk, we’ve encountered a wide array of myths that can discourage talented individuals or mislead those exploring a data science career. This article aims to bust the top 10 data science career myths—providing clarity on what data scientists actually do and illuminating the true diversity and inclusiveness of this exciting field. Whether you’re a recent graduate, a professional looking to pivot, or simply curious about data science, read on to discover the reality behind the myths.

Global vs. Local: Comparing the UK Data Science Job Market to International Landscapes

How to evaluate salaries, opportunities, and work culture in data science across the UK, the US, Europe, and Asia Data science has proven to be more than a passing trend; it is now a foundational pillar of modern decision-making in virtually every industry—from healthcare and finance to retail and entertainment. As the volume of data grows exponentially, organisations urgently need professionals who can transform raw information into actionable insights. This high demand has sparked a wave of new opportunities for data scientists worldwide. In this article, we’ll compare the UK data science job market to those in the United States, Europe, and Asia. We’ll explore hiring trends, salary benchmarks, and cultural nuances to help you decide whether to focus your career locally or consider opportunities overseas or in fully remote roles. Whether you’re a fresh graduate looking for your first data science position, an experienced data professional pivoting from analytics, or a software engineer eager to break into machine learning, understanding the global data science landscape can be a game-changer. By the end of this overview, you’ll be better equipped to navigate the expanding world of data science—knowing which skills and certifications matter most, how salaries differ between regions, and what to expect from distinct work cultures. Let’s dive in.