Senior Technical Information & Data Analytics Manager

Nomad Foods Inc; Lowestoft; On-site; GBP 45,000 - 85,000; Full time

Job description

Overview

Leads setting and delivering the strategy for technical data systems and specifications in RDQ, covering the complex, multi-layered specification elements that deliver the 7000 SKUs delivering €3.2bn NS. Manages Interspes and RDQ input into this system along with interfaces with SAP and SU systems and teams across all sites.

Leads PLM/Intraspec strategy for RDQ, this will be a new end-to-end project/data management tool connected to SAP which will require process understanding, leading the technology solution with IT, implementation management, and change management.

Leads strategy and deployment of RDQ Knowledge management systems, seeking ways to optimise RDQ data analytic capability, improving speed and effectiveness of data for RDQ programs and reporting.

This role is instrumental in implementing robust data analytics capabilities, technical specification management, and ensuring R&D workflows are optimised across the product lifecycle.

Responsibilities

Leads RDQ Technology strategy (including where relevant AI) and delivery, preparing RDQ to be fit for purpose with this technology.

Deliver accurate and timely technical data and specifications across the technical data portfolio, ensuring the RDQ tasks are complete and compliant. Optimise how Interspec (and future PLM) can be used by RDQ and its interface with S4Hana. Collaborate with cross-functional teams to establish processes for updating specifications, ensuring compliance with regulatory standards, and supporting product adjustments or improvements.

Data and information as an enabler in RDQ

Develop and deliver a data strategy for RDQ on Data Analytics (including how to manage and resolve effectively), Knowledge Management systems, and how to deploy Artificial Intelligence most effectively. Enable insights in process optimisation and performance tracking.

Deliver the future of technical data in RDQ

Oversee technical assessments of new tools and technologies that enhance R&D capabilities. Lead the strategy and delivery of PLM for RDQ, including change management from Interspec to a new system. Liaise closely with RDQLT members to specify what a new data system must deliver and with IT/External experts to specify this. Seek external experience of similar systems to facilitate the best solution for Nomad Foods.

RDQ Leadership and Governance

Build and lead a high-performing team of data scientists and analytics, fostering a culture of innovation, continuous improvement, and collaboration.

R&D Technical Information & Data Analytics Lead

Responsible for developing capability of own resources, managing career development of teams within the work area through excellent line management skills and coaching. Responsible for recruiting and deploying resources and budget in the most effective way to deliver targets, including shared targets across the RDQLT. Member of the RDQLT and works in a highly collaborative way with fellow LT members under guidance from the Chief RDQ Officer to deliver RDQ commitments to the Business, Strategic Plan, and Annual Plan. Responsible for governance and management of project portfolio in own area.

Contribution to Quality

Performance quality is the responsibility of everyone in RDQ and the RDQ leadership team sets the example and drives the mindset. From Design For Manufacture and Quality By Design principles, through to Right First Time delivery of projects and data, the Leader ensures quality ways of working are consistent in actions across their team.

Qualifications

• A strong background in data analytics, data science, and technical operations
• Minimum degree in a technical science
• 3+ years of experience in data analytics within FMCG
• Experience in SAP/ERP systems (and evidence of PLM)
• Proficiency in statistical analysis software, data strategy, and strong communication skills, with the ability to translate technical data into business insights.
• Modelling is a plus
• Experience with machine learning and predictive analytics