Organisation Data Integrity Lead

Unilever
Leeds
1 week ago
Create job alert

We are currently seeking an interim Organisation Data Integrity Lead, to work with our global FMCG client Unilever, renowned for brands such as Dove, Sure, Persil, and Simple, to become an integral part of their fast-paced FMCG environment.


The position is fully remote (UK Only) This is a part-time temporary role to last until end December 2025, requiring 21 hours and 45 minutes per week, working Monday to Friday. Compensation for this role is competitive, paying up to £73,000 (Full time Equivalent) per annum, pro rata, depending upon experience


Summary:We seek a visionary and experienced Team Lead to fully own the data and structural integrity of our Productivity Org design. This critical role is essential for managing change requests and meeting our market commitments. You will lead a dedicated team of Data Analysts, driving excellence in CR evaluation, data integrity, and high-quality business support and analysis.


Main Tasks and Responsibilities:

  1. Ensure data and structural integrity of the design and deliver data-driven insights & analyses to the Business:
  • Data Excellence & integrity:Maintain impeccable data integrity and quality, supporting informed and strategic business decisions.
  • Data-Driven Insights:Comprehensive data analysis empowers Business Teams and the control tower to make strategic Steerco decisions.
  • Strategic Business Support:Deliver exceptional business support and data analysis, driving success and achieving market commitments.
  • Data-driven Escalations:Critical issues are escalated effectively, ensuring swift resolution.
  • Seamless CR Management:Efficiently manage and optimize the change request process, ensuring timely and accurate implementation.
  • Enhanced Accountability:Ensure that Change requestors are held accountable, fostering a culture of responsibility.
  • Innovative Solutions:Continuously identify and implement optimization opportunities, enhancing our processes (Change Request, Employee Tracking, etc.) and tools (to be launched WebApp).


Leading the D&A Team:

  • Aligned Priorities:Ensure that change requests and related activities are prioritized effectively and align with business goals.
  • High Team Motivation:The team remains motivated and consistently delivers high-quality results.
  • Effective Moderation:Conflicts between the D&A team and Business Teams are moderated, escalated, or de-escalated as needed, fostering a collaborative environment


Goals and KPIs:

  • Streamlining the CR processing via a to-be-launched WebApp (April) and ensuring high WebApp Adoption:Achieve a 90%+ adoption rate for the automated WebApp solution.
  • Efficient CR Processing:80+% of all CRs are processed via the WebApp, enhancing operational efficiency.
  • Timely and Accurate CR Evaluation:All remaining Change Requests (CRs) are promptly evaluated, correctly implemented, and meticulously documented for auditing purposes, ensuring compliance with CT requirements.
  • Continuous WebApp Optimization:Regularly identify and prioritize optimization opportunities through customer surveys, implementing improvements within budget. Prepare detailed business cases for additional budget requirements.
  • Efficient CR Process:Establish and maintain an efficient change request process, continuously optimizing based on customer feedback and securing approvals from CT.
  • Effective Cost Management:CHROs and their teams manage savings and landing org cost/FTE commitments through WebApp.
  • Seamless Data Transfer:Successfully transfer productivity data into the new Workforce Planning Process standard by Q3/4, ensuring smooth integration.


Tools and Technologies:

  • Excel TM files
  • Databricks-based WebApp solution (will be trained during onboarding)


Qualifications and Experience:

  • Strategic Prioritization:Strong ability to set priorities and motivate the team, driving high performance and successful outcomes.
  • Proven Leadership:Demonstrated experience in leading & inspiring a small team to achieve exceptional results.
  • Exceptional Communication Skills:Effective and diplomatic communication and moderation abilities, fostering collaboration and resolving conflicts.
  • Excellent systems experience using MS Excel

Related Jobs

View all jobs

Organisation Data Integrity Lead

Organisation Data Integrity Lead

CRM Systems Manager

Python/Data Science Developer

Senior Data Manager

Qualified Person (QP) - Pharmaceutical

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.

Careers

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.

Careers

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.

Careers

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.

🍪 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.