Senior Operational Data Analyst

No7 Beauty Company
2 months ago
Applications closed

Related Jobs

View all jobs

Finance Data Analyst

Senior Data Analyst

Senior Data Analyst, AGI-DS RAMP

Inventory Data Analyst

Business Data Analyst

Data Analytics Manager

Job Title:Senior Operational Data Analyst

Location: Nottingham

Contract: Perm

About the role

Our Operational Analytics team supports the business to make smarter data-based decisions. We focus on agile working, continuous improvement, and personal development. As the business becomes more focused on data and technology, we evolve too with more complex data utilization and providing analytics-backed value.

Understand the business as a specialist and support the business with driving change, commercial decisions, and supporting the business to evolve backed by a data-driven approach. Delivering business needs and requirements to be able to provide different outputs, e.g., Data, Reporting, Analytics, Insight, etc. Utilising a problem-solving mindset and technical expertise in tools such as Power BI, Azure DataBricks, etc.

Become a subject matter expert for part of the business and support the business with driving change, commercial decisions through data analysis, reporting, insights, and drive on customer self-serve capabilities.

  • Work with the business to understand the business and deliver reporting, analytics, and insight expectations
  • Build, maintain, and manage stakeholder relations across business functions
  • Perform data ETL from various sources/systems into Power BI/Alteryx
  • Working in an Agile manner provide accurate, cross-business functions aligned outputs
  • Support maintenance of live infrastructure for data, reporting, and analytics
  • Drive capabilities development while instilling a self-serve culture
  • Show out-of-the-box thinking and eye for opportunities when looking at potential problems
  • Support the Analytics manager to deliver long-term business objectives and support with the development of the team

What you’ll need to have

These are the essential skills or experience needed to succeed in this role.

  • Advanced knowledge and technical experience with Power BI reporting and analytics (along with other MS Packages e.g., Power Automate)
  • Intermediate working knowledge of Azure DataBricks and programming languages like Python, SQL, etc.
  • Knowledge of statistical, financial, and commercial analytics techniques e.g., a/b testing, mix variance analysis, etc.
  • Experience of data modeling to assess profitability and impact analysis
  • Experience of turning various data sets into outputs to drive commercial value
  • Experience of organizing and setting up data for advanced analytics models
  • Stakeholder relationship management
  • Curious, analytical problem-solving mindset
  • Commercial acumen to understand raw data and present the story as output
  • Ability to map processes and document data and models/reporting
  • Be able to simplify and explain complex technical models and outputs to key business stakeholders

It would be great if you also have

These are desirable skills or experience and are not essential, so we would welcome applications from candidates that don’t match this additional criteria.

  • Expertise in other systems/tools such as Alteryx, R, etc.
  • Working knowledge of commercial business areas like Sourcing, Product quality, sustainability, etc.
  • Agile Project management

Why Boots

At Boots, we foster a working environment where consideration and inclusivity help everyone to be themselves and reach their full potential. We are proud to be an equal opportunity employer, passionate about embracing the diversity of our colleagues and providing a positive and inclusive working environment for all. As the heart of everything we do at Boots, it's with you, we change for the better.

What's next

Where a role is advertised as full-time, we are open to discussing part-time and job share options during the application process. If you require additional support as part of the application and interview process, we are happy to providereasonable adjustmentsto help you to be at your best.

This role requires the successful candidate to complete aPre-employment checkafter receiving an offer. Depending on your location you will be asked to submit either a DBS (Disclosure & Barring Service), PVG (Protection of Vulnerable groups), or an Access NI Check.

Boots is a Ban the Box employer and will consider the suitability of applicants with criminal convictions on a case-by-case basis.

#J-18808-Ljbffr

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.

Jobs

Portfolio Projects That Get You Hired for Machine Learning Jobs (With Real GitHub Examples)

In today’s data-driven landscape, the field of machine learning (ML) is one of the most sought-after career paths. From startups to multinational enterprises, organisations are on the lookout for professionals who can develop and deploy ML models that drive impactful decisions. Whether you’re an aspiring data scientist, a seasoned researcher, or a machine learning engineer, one element can truly make your CV shine: a compelling portfolio. While your CV and cover letter detail your educational background and professional experiences, a portfolio reveals your practical know-how. The code you share, the projects you build, and your problem-solving process all help prospective employers ascertain if you’re the right fit for their team. But what kinds of portfolio projects stand out, and how can you showcase them effectively? This article provides the answers. We’ll look at: Why a machine learning portfolio is critical for impressing recruiters. How to select appropriate ML projects for your target roles. Inspirational GitHub examples that exemplify strong project structure and presentation. Tangible project ideas you can start immediately, from predictive modelling to computer vision. Best practices for showcasing your work on GitHub, personal websites, and beyond. Finally, we’ll share how you can leverage these projects to unlock opportunities—plus a handy link to upload your CV on Machine Learning Jobs when you’re ready to apply. Get ready to build a portfolio that underscores your skill set and positions you for the ML role you’ve been dreaming of!

Jobs Careers

Machine Learning Job Interview Warm‑Up: 30 Real Coding & System‑Design Questions

Machine learning is fuelling innovation across every industry, from healthcare to retail to financial services. As organisations look to harness large datasets and predictive algorithms to gain competitive advantages, the demand for skilled ML professionals continues to soar. Whether you’re aiming for a machine learning engineer role or a research scientist position, strong interview performance can open doors to dynamic projects and fulfilling careers. However, machine learning interviews differ from standard software engineering ones. Beyond coding proficiency, you’ll be tested on algorithms, mathematics, data manipulation, and applied problem-solving skills. Employers also expect you to discuss how to deploy models in production and maintain them effectively—touching on MLOps or advanced system design for scaling model inferences. In this guide, we’ve compiled 30 real coding & system‑design questions you might face in a machine learning job interview. From linear regression to distributed training strategies, these questions aim to test your depth of knowledge and practical know‑how. And if you’re ready to find your next ML opportunity in the UK, head to www.machinelearningjobs.co.uk—a prime location for the latest machine learning vacancies. Let’s dive in and gear up for success in your forthcoming interviews.

Jobs

Negotiating Your Machine Learning Job Offer: Equity, Bonuses & Perks Explained

How to Secure a Compensation Package That Matches Your Technical Mastery and Strategic Influence in the UK’s ML Landscape Machine learning (ML) has rapidly shifted from an emerging discipline to a mission-critical function in modern enterprises. From optimising e-commerce recommendations to powering autonomous vehicles and driving innovation in healthcare, ML experts hold the keys to transformative outcomes. As a mid‑senior professional in this field, you’re not only crafting sophisticated algorithms; you’re often guiding strategic decisions about data pipelines, model deployment, and product direction. With such a powerful impact on business results, companies across the UK are going beyond standard salary structures to attract top ML talent. Negotiating a compensation package that truly reflects your value means looking beyond the numbers on your monthly payslip. In addition to a competitive base salary, you could be securing equity, performance-based bonuses, and perks that support your ongoing research, development, and growth. However, many mid‑senior ML professionals leave these additional benefits on the table—either because they’re unsure how to negotiate them or they simply underestimate their long-term worth. This guide explores every critical aspect of negotiating a machine learning job offer. Whether you’re joining an AI-focused start-up or a major tech player expanding its ML capabilities, understanding equity structures, bonus schemes, and strategic perks will help you lock in a package that matches your technical expertise and strategic influence. Let’s dive in.

🍪 We use cookies to enhance your browsing experience on our website. By continuing to use this site, you consent to the use of cookies as described in our Cookie Policy. You can review our Cookie Policy for more information.