Do you want to help deliver AI at scale for the world’s largest jewellery brand? Do you have experience with building and scaling Data & Analytics products across the value chain? And do you know what it takes to productionize ML models, grow a team of ML Engineers and deliver business outcomes through Advanced Analytics? Then we have a job for you.
We’re on a mission to turn data into business value and are now looking for an experienced Machine Learning Engineering Manager to help drive the future of our team and scale our Data & Analytics Center of Excellence to the next level. The ideal candidate will have solid experience in building and scaling enterprise level ML applications, improve speed-to-production and secure scalability and robustness of systems and pipelines. In addition to a solid technical background our future Manager will come with extensive experience building and leading software development and engineering teams.
In this role your key accountabilities will be to:
- Lead deployment and scaling of ML models across the value chain by working closely with product management teams to ensure product deliverables, timelines and KPIs are met.
- Serve and partner with stakeholders as senior SME on ML technology at scale.
- Provide guidance and oversight for engineering teams to solve complex multi-disciplinary challenges, designing distributed systems and software architectures for scalability, reliability and performance.
- Accountable and responsible for data & analytics end-to-end.
- Build and nurture a results-driven team culture to ensure effectiveness of products and teams.
- Build organizational capabilities by attracting, developing and retaining a team of world-class ML Engineering talent.
- Collaborate with the Data Science team and the wider Digital and Technology organization to evolve the data architecture to support better integration, deployment and platform tools to support ML Engineering.
- Improve velocity and delivery through best-practice engineering and agile methodology.
- Implement agile software development principles, DevOps and MLOps.
- Develop architectural standards together with the wider engineering and technology community.
What is needed to succeed
- An advanced degree in engineering, computer science, software development or similar.
- Excellent written and oral communication skills with an ability to explain complex engineering concepts to stakeholders in other engineering and analytics teams, product management etc.
- 5+ years of professional software engineering and machine learning experience, 2+ years of experience in building and managing software engineering teams responsible for delivering, scaling and productionizing data and analytics products.
- Track record of recruiting and retaining software engineering and data and analytics talent.
- Experience in developing and delivering data and analytics products through POC, MVP through to production and maintenance, working closely with data science and technology teams.
- Experience in orchestrating workflows and pipelines using Airflow, Azure Data Factory or other.
- Experience with MLOps practices for CI/CD/CT and other concepts specific to the ML model lifecycle incl. real-time analytics use cases.
- Experience with feature engineering for ML and predictive models.
- Experience working with Azure and or AWS cloud infrastructure, IaC, IaaS and PaaS.
- Advanced knowledge of databases and engineering concepts with hands on experience with one or more data analytics/programming tools such as Hive/SQL/Spark/Python and analytics PaaS like Databricks and Synapse.
- Full stack development experience and knowledge in building APIs, microservice, publish-subscribe systems and messaging services e.g. Event Grid, Event Hub, Kafka, Service Bus is an extra bonus.
- Industry presence and thought leadership through published research, blogging, conferences, meetups, open source contributions.
- Outcome driven mindset with a solid always-be-shipping mentality .
Something about you
How would you rate yourself on the 4 C’s? We believe that communication, collaboration, critical thinking and creativity are key competences that will help anyone regardless of job function, title or skillset, in becoming a success. If you can see yourself working in a fast-paced entrepreneurial environment with many stakeholders, where your communication and interpersonal skills are needed and your ability to collaborate and innovate as a team is essential, we would love to hear from you.
Your new team
Say hello to the Advanced Analytics team in the Data & Analytics Center of Excellence at Pandora – the world’s largest jewellery brand. We are a group of 19 data-driven professionals who support business units across the full value chain with actionable insights and predictive analytics. We have a data lake, a unified analytics platform and solid communication skills that help us translate data into business value. Your new team consists of a diverse and happy group of analysts, scientists, engineers and product people with a clear mission: We are here to deliver data-driven experiences in all consumer journey touchpoints, develop actionable insights to inform business decisions across supply chain, product, marketing, commerce, finance, HR and more – and have fun while doing it.