- Information Technology
- Bristol, Malmesbury - United Kingdom
Data and analytics excellence at Dyson are delivered by a diverse and collaborative global community spread across Dyson locations from Bristol to Chicago, Malmesbury to Singapore. Domain-specific experts form spoke analytics teams, enabled by a central team at the hub. All teams benefit from significant recent investments in cloud technologies and tools, combined with an expansive scope and no shortage of ambition and momentum; data and analytics are recognised throughout the organisation, to the highest level, as critical to all of Dyson’s strategic objectives. With a ‘one-team’ approach, the global community are on a mission to…
- …evolve existing solutions to stay ahead
- …embed emerging solutions to capitalise on potential benefits
- …deliver conceptualised & future solutions to introduce net-new capability
Our Data Team
As the ‘hub’ team delivering the data, technology and community provision enabling Dyson’s global data and analytics capabilities, Global Data Function (GDF) have end-to-end responsibility for data from foundations (DQ, MDM) to management (data platforms, integrations), to value realisation (analytics enablement and delivery). The team is a multi-disciplinary, global team providing round-the-clock development and operations – including product and project management, community enablement, governance, data architecture, data engineering, data science, and analytics expertise. Involved with every aspect of Dyson’s global business - from finance to product development, manufacturing to owner experience – data is enjoying record-breaking investment and mandate for 2021 and beyond, seeking to deliver solutions generating impressive and tangible business value.
About the roleThe role
You will have hands on experience with various type of data warehouse, and a keen understanding of data models, SQL, and ETL processes. Using tools like R, Python, and Tableau you are able to analyse, model, and visualise data effectively. Ideally you will have an MSc or PhD in a relevant field (e.g. Statistics, Mathematics) or similar hands-on experience.
- You will help respond to complex business questions beyond what business intelligence teams are capable of today.
- You will build predictive models using a myriad of data sources available at Dyson. Often using Dyson’s vast data sets and sometimes making smart decisions on how to best use small data sets from inside or outside the organisation.
- You will apply logical thinking and statistical learning techniques to obtain robust results the business can rely on for critical decisions.
- You will engage with the business and data product managers to shape and refine their questions.
- You will team up with Data Engineers and Data Product Managers to get advice and support on accessing data.
- Cutting edge approaches are key to keeping pace with Dyson’s innovative culture. You will be expected to stay abreast of industry trends and emerging technologies and methodologies.
About youPerson specification / Core Competencies:
- A degree in Statistics/ML/Business Analytics or a science/engineering degree with a keen interest in statistics.
- Python skills with a focus on statistical and ML packages; Scikit-Learn, XGBoost, NumPy, SciPy, Tensorflow, Keras, PyTorch.
- Experience in data cleansing and blending (internally and externally) to drive richer insights.
- Scientific approach to solve practical problems, logical thinking. Advanced data modelling skills.
- Basic knowledge on how to build data science products in cloud environments. Comfortable querying modern cloud databases (e.g. BigQuery, Snowflake, Redshift).
- Passion to understand the business, frame problems, and deliver practical solutions on short time frames
- Self-driven individual with drive to solve customer problems. Team player and good communicator within the team and beyond, capable of building great stories our of sparse data
- PhDs are valued, but innovation and excellence is essential
- Ability to interact and collaborate with data engineers and product manager
- Docker and Kubernetes experience
- Successful use of software engineering best practices, including version control (Git, Mercurial), unit testing and working with Agile delivery principles.
- Fullstack experience in data collection, aggregation, analysis, visualisation, productionisation, and monitoring of ML products - aka MLOps
- 27 days holiday plus eight statutory bank holidays
- Pension scheme
- Performance related bonus
- Private medical insurance
- Life assurance
- Sport centre
- Free on-site parking
- Subsidised café and restaurants
- Discounts on Dyson machines
We are following the government guidelines regarding COVID19. At this time all interviews will be conducted via video or telephone. We’re taking these precautionary measures to protect both our employee and candidate wellbeing. Our Talent Acquisition team will work with you and provide further information as appropriate.