R&D Senior Associate - Data Lead & CI

Reckitt Benckiser Group plc.

R&D Senior Associate - Data Lead & CI

Salary Not Specified

Reckitt Benckiser Group plc., Kingston upon Hull

  • Full time
  • Permanent
  • Onsite working

Posted 2 weeks ago, 16 May | Get your application in now before you miss out!

Closing date: Closing date not specified

job Ref: 2a6d9b539e744bf6af85826e81de08d0

Full Job Description

Home to the world's best loved and trusted hygiene, health, and nutrition brands. Our purpose defines why we exist: to protect, heal and nurture in the relentless pursuit of a cleaner, healthier world. We are a global team united by this purpose.

Join us in our fight to make access to the highest quality hygiene, wellness, and nourishment a right and not a privilege.

Research & Development

In R&D, we're full of highly skilled talents that include Scientists, Engineers, Medical, Clinical and Regulatory professionals - all working to create a cleaner, healthier world. With nine Centres of Excellence, we continually seek out new opportunities by using science, our entrepreneurial flare and our fearless innovation to develop and enhance our existing portfolio, never compromising on quality or performance.

We do the right thing, always, by ensuring we act with responsibility and integrity, by complying with regulatory legislation across the globe, whilst ensuring our products are safe for our consumers and are to the highest quality.

The size of our organisation means you'll have the opportunity to learn and work in different functions within R&D, giving you exposure to different disciplines, teams and environments. You will also have access to our R&D Academy, designed to develop our team and allow you to grow in our great organisation.

About the role

The role is ideal for a high-calibre individual with the necessary skill set to lead a team of data scientists/analysts working on a cross-functional platform of projects and initiatives spanning but not limited to data insights, behavioural analytics, productivity improvement, minimising process waste, automation activities and statistical process modelling to drive data driven decision making.

The challenging role comprises of leading a team of data scientists/analysts - both from a managerial and technical excellence point of view - whilst dealing with a multitude of challenging and ever-changing situations and stakeholders.,

  • Data and Continuous Improvement Lead within R&D Operations

  • Working with team managers, project managers and associates to deliver effective solutions to complex challenges.

  • Support statistical activities across R&D Operations, providing pivotal data insights whilst simplifying processes and reports (such as KPIs).

  • Accountable for the delivery and execution of project work of your team

  • Automation and digitisation (AI/ML opportunity development) for R&D Operations

  • Data modelling and simulation toolkit development (in collaboration with technical team peers and IT&D)

    Minimum of a good degree in a relevant scientific discipline (e.g. Chemistry, Pharmaceutical Science, Chemical Engineering, Biology, Biochemistry)

  • Post graduate qualifications in further scientific disciplines would also be beneficial (i.e. PhD, or MSc, post-graduate diplomas (e.g. Pharmaceutical Quality by Design)

  • Experience in project and stakeholder management.


  • The candidate should be comfortable with ambiguity and be a 'self-starter' with the ability to quickly learn and implement to keep up with the fast pace of the role.

  • Technically diligent and able to grasp new science and visualise a business benefit.

  • Ability to delegate but still be accountable.

  • Prioritisation and time management skills are essential.

  • Stakeholder collaboration and the ability to manage expectations are also key.


  • The skills for success

    Task Execution Under Pressure, Makes strategic Business Decisions, Business Acumen, Commercial Awareness, Objective Setting, Accountability, Creative Direction, R&D, Change Leadership, Product Lifecycle Management, Business Partnership, Collaboration and partnership building, Relationship Management, Adapt to changes in technological development plans, Ability to challenge the status quo and propose improvement, Innovation Processes, Digital transformation for R&D, Quality and Manufacturing, Data insights.