Job Description:
Royal Canin is undergoing a significant Digital Transformation journey. Our ability to solve the most critical problems across Mars in a User Centric way through Data & Analytics is fundamental to our growth ambition and transformation. Significant early success in this journey, and the introduction of many critical foundational capabilities, means that we are looking to accelerate our ability to solve problems and ultimately drive value for Mars Inc.
The opportunities are significant for Mars, and the opportunities for those working in this space are both hugely exciting and rewarding. Connecting and deriving break-through insight from our Royal Canin and Petcare data ecosystems, leveraging the rapidly growing world of external data to get closer to our customers and consumers than ever before, and unlocking efficiencies and automation across our End-To-End Value Chain.
Building on this momentum, we are recruiting a Machine Learning and AI Engineering Lead to join our Royal Canin Global Data & Analytics Team who will accelerate the shaping and delivery of our Data & Analytics Agenda.
The Machine Learning and AI Engineering Lead will oversee ML and AI solution development and deployment as a capability served across the end-to-end Data & Analytics solution portfolio. The role integral to the organization's mission of leveraging advanced technologies to drive innovation and efficiency across the organisation. The role will work closely with the Data Science Lead to develop and execute an AI and ML roadmap aligned with business goals and requirements.
What will be your key responsibilities?Serve as the technical lead for Generative AI and machine learning model deployment within RC D&A.
Collaborate with the Data Science team to design, prototype and build next generation ML and AI products and accelerators.
Design, architect and review technical architecture for data science, machine learning and AI solutions and provide feedback for optimal implementation.
Develop and oversee the implementation of an MLOps and LLMOps strategy. Align and contribute towards the wider Petcare MLOps strategy.
Review code developed by the data science team to ensure solution can be deployed. Identify opportunities to optimize methodologies.
Contribute to a high performing data science function through coaching data scientists and providing training on writing scalable code and good software engineering practices.
Create repeatable, interpretable, dynamic and scalable model training pipelines that are incorporated into analytic data products through cloud web applications and APIs.
Define key performance indicators (KPIs) and implement monitoring systems for deployed products to ensure continuous operational performance. Define strategy to handle incident management.
Engage with RC D&A Platform Lead and Platform Product Owner to scope, plan and implement accelerators.
Stay updated with the latest advancements in MLOps. Apply relevant techniques into projects. Educate D&A on technological advancements in this area.
Documentation: Maintain comprehensive documentation for model training pipelines, deployment processes, and code.
Partner with the Product Management squad model and provide advice on how inflight projects can utilise ML and AI to generate additional value.
5-7 years of experience working in a quantitative role preferably in the CPG, or retail industry.
Proven track record of delivering value through AI/ML/Data Science products in a fast-paced, agile environment using a scalable and reusable codebase and models to address business problems effectively.
Partner with business leadership across functions and data science teams to identify business challenges and opportunities and translate them unto actionable, integrated, data-driven solutions.
Eagerness to learn, flexibility to pivot when needed, savviness to navigate and thrive in a dynamic environment, and a growth mindset needed to build a successful team
A strong customer centric mindset especially within an internal customer base with the purpose of driving value creation, adoption and use
Strategic thinking, problem solving and innovation, with the ability to anticipate and navigate challenges and opportunities.
Ensure compliance with analytics standards, including tailoring methodologies to specific use case needs such as ML, AI, and descriptive analytics.
Ability to translate business needs into analytical frameworks & superior verbal and written communication skills
Working understanding of ML Ops and DevOps frameworks
Familiarity with Microsoft Azure tech stack, including but not limited to AzureML, Azure AI Foundry, Databricks
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.
Best-in-class learning and development support from day one, including access to our in-house Mars University.
An industry-competitive salary and benefits package, including company bonus.
#TBDDT
