At a Glance
- Tasks: Lead digital transformation in R&D, focusing on data integrity and process mapping.
- Company: Join Mars, a global leader in the food industry with a commitment to innovation.
- Benefits: Competitive salary, bonuses, and access to Mars University for continuous learning.
- Other info: Collaborative environment with opportunities for growth across diverse teams.
- Why this job: Make a real impact on R&D processes while working with cutting-edge technology.
- Qualifications: Detail-oriented with strong analytical skills and experience in data modelling.
The predicted salary is between 63000 - 77000 £ per year.
- Job ID: R168870Company: Mars
- Category: Data, Analytics & Insights
- Industry: Food Manufacturers
- Level: COMP_Job_Level_T3Posted: 2026-11-02
Job Description
Job Purpose/Overview
Check out the role overview below If you are confident you have got the right skills and experience, apply today.
We require a highly skilled and experienced professional to independently lead and drive the Corporate R&D Process and Systems team's digitalization efforts.
This role is critical to advancing a global, cross-segment R&D digital transformation program, enhancing efficiency, speed, and future-proofing our business.
The role will report directly into the Digital Core Q&FS/R&D pillar and will extend its scope to include Quality & Food Safety (Q&FS) and other R&D Edge capabilities-related activities.
The successful candidate will take ownership of the data and process related activities in relation to Enterprise Digital Core capabilities, including Quality Management (Testing & Conformance, Inbound and Outbound Traceability), Product Lifecycle Management (PLM), and seamless integration with Product Portfolio Management (PPM).
These Enterprise R&D Digital capabilities will be deployed in all Royal Canin business units through the EOS program.
This position requires a strategic thinker and a technical leader who will collaborate with senior stakeholders across RC and Enterprise to ensure data integrity, compliance, and alignment with Mars' business objectives.
The Corporate R&D/Q&FS Digital Core Data Champion is responsible for supporting the operational work related to activities managing R&D Master Data modeling, data requirement gathering and integration design.
Collaborate with the Digital Core Data Manager to create and execute the data migration (ETL) strategy and the operational data governance efforts across R&D Edge, Core Quality (S4 & MDG), PPM and R&D Analytics.
This role will be involved in the development and implementation of data models and integration processes to ensure data integrity, consistency, and quality across all business functions and compliant with regulations.
This role will be a crucial part of the process mapping efforts in Signavio, developing and maintaining detailed process maps for all R&D Edge and Q&FS activities, including material master data management, product lifecycle management, and quality control workflows.
This role is expected to work in partnership with the DT Data modelling solution architect, the Corporate R&D Material Master Data Champions, the Corp R&D Digital Core Senior leaders (Quality, Cplm, Process, SRA, Supply, SQA), the Segment Systems representatives and SMEs and the Functional Experts.
This role is transformation funded and has an expected length of around 3 years.
What will be your key responsibilities?
- STAKEHOLDER ENGAGEMENT
- Collaborate with stakeholders to gather functional data requirements, in order to develop and implement a comprehensive data modeling blueprint
- Collaborate with stakeholders to gather functional process requirements, in order to develop a detailed business process map in Signavio
- Help to create stakeholder updates such as newsletters, roadmap updates
- Help facilitate the connection with Sustainability, Regulatory Affairs, Trade Compliance, Commercial etc .
- R&D MASTER DATA MODELING
- Lead the creation and evolution of a data modeling blueprint that incorporates best practices and innovative solutions
- Define and enforce data modeling standards, policies, and procedures to ensure consistency and quality across the R&D data ecosystem.
- Establish and oversee data governance practices for master data, including data stewardship, data quality, and metadata management.
- Stay at the forefront of data modeling techniques and technologies and drive the adoption of innovative solutions to enhance the R&D data infrastructure.
- Continuously evaluate and refine data models to improve data accuracy, accessibility, and utility for analytics and reporting.
- DATA REQUIREMENT GATHERING, DATA MIGRATION (ETL) STRATEGY AND TOOLSET
- Lead activities and procedures such as capturing data definitions and data owners on the Data Wiki.
- Leading segment data harmonization activities in Veritas to support Digital Core
- Support operational data quality work in R&D across Q&FS, ERP and other capabilities
- Support requirement gathering and translation from SRA, SQA, Quality, Product and Pack Developper, Supply, Sustainability, Finance, to ensure data compliance with regulatory and sustainability principles
- Support cross-functional data related decisions and collaborate in data related design and governance
- Create analysis to ensure accurate specifications for materials to be purchased, including raw materials, semi-finished goods, and finished products, especially related to the necessary data consolidation in RC
- PROCESS MAPPING FOR Q&FS AND R&D
- Help to develop and maintain detailed process maps for all R&D Edge and Q&FS processes and analytics, including material master data management, product lifecycle management, and quality control workflows.
- Ensure process maps are aligned with Mars' global standards and regulatory requirements.
- CONTINUOUS IMPROVEMENT & DEPLOYMENT
- Create and maintain user-friendly documentation and training materials to facilitate the adoption of new data models and data assessment and data migration processes
- Document data definitions and attributes in a central repository (Mars wiki).
- Create and maintain regular or one-off Data Quality and/or Data Validation analysis.
- Promote a culture of continuous improvement, encouraging the team to seek out and implement process enhancements.
- Drive innovation by exploring new tools, methodologies, and approaches to enhance the data modelling process, data cleansing, data migration, data quality.
What are we looking for?
- Detail-oriented with strong analytical and problem-solving abilities.
- Ability to collect and translate business needs into technical requirements.
- Excellent verbal and written communication skills. Fluent in English.
- The ability to work effectively in a cross-functional team environment.
- Proactive and self-motivated with a strong sense of ownership.
- Being able to work independently and take initiative – strong ability to work in a virtual environment across multiple time zones and cultures.
What can you expect from Mars?
- Work with diverse and talented Associates, all guided by the Five Principles.
- Join a purpose driven company, where we're striving to build the world we want tomorrow, today.
- A strong focus on learning and development support from day one, including access to our in-house Mars University. xgikmsk
- An industry competitive salary and benefits package, including company bonus.
Corporate R&D Digital Core Q&FS Product & Quality Data Champion in High Wycombe employer: Mars
Mars in Melton Mowbray is an exceptional employer, offering a dynamic work culture that fosters innovation and collaboration. With competitive salaries, private healthcare, and ample opportunities for career advancement, employees are encouraged to grow and thrive in their roles while working with state-of-the-art technology in the FMCG sector.
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We think this is how you could land Corporate R&D Digital Core Q&FS Product & Quality Data Champion in High Wycombe
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We think you need these skills to ace Corporate R&D Digital Core Q&FS Product & Quality Data Champion in High Wycombe
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
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Craft a Tailored Cover Letter:For a full-time role at Mars, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Mars. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at Mars
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
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Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
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✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
