- Data Science and Engineering
- Singapore - Technology Centre
Data & Analytics at Dyson
Data and analytics excellence at Dyson are delivered by a diverse and collaborative global community spread across Dyson locations from Bristol to Chicago, Shanghai 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 is recognised throughout the organisation, 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 have end-to-end responsibility for data from foundations (DQ, MDM, Compliance) 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 role
You will have hands-on experience with leveraging data from a wide selection of data sources from different technologies e.g. SQL db, BigQuery, etc., and a keen understanding of data models and ETL processes. Using tools like R, Python, and any visualisation tools (when required), 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 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 help respond to complex business questions beyond what business intelligence teams are capable of today.
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.
Person Specification / Core Competencies
A drive and know-how to deliver tangible business value through data science models
Scientific approach to solve practical problems using logical thinking.
Passion to understand the business, frame problems, and deliver practical solutions in short timeframes.
Ability to interact and collaborate with Data Engineers, Data Architects and Data Product Manage
Self-driven individual with drive to solve customer problems. Team player and good communicator - capable of building great stories out of sparse data.
Good presentation and communication skills, with the ability to explain complex analytical concepts to business audiences
A degree in Statistics/ML/Business Analytics or a science / engineering degree with a keen interest in statistics.
PhDs are valued, but innovation and excellence is essential
Strong understanding of statistical modelling. Working experience of using advanced machine learning techniques to solve business challenges.
Strong R/Python skills with a focus on statistical and ML packages; e.g. Scikit-Learn, Tensorflow, Keras, PyTorch, XGBoost, NumPy, SciPy.
Working experience with cloud-based platforms. Comfortable querying modern cloud databases (e.g. BigQuery, Snowflake, Redshift).
Successful use of software engineering best practices, including version control (Git, Mercurial), unit testing and working with Agile delivery principles.
Proven track-record of using a rigorous, scientific approach to model building, testing and validation.
Experience in data cleansing and blending (internally and externally) to drive richer insights.
Knowledge of how to build enterprise data science products in cloud environments
Docker and Kubernetes experience
Experience productionising data science models that deliver demonstrable business value
Exposure to ML Ops practices and thinking
Familiar with Linux/Unix and shell scripting, experience in cloud computing is a plus
Data visualization and app development techniques (Shiny, Dash, App Engine)
Dyson monitors the market to ensure competitive salaries and pension contributions. Beyond that, you’ll also enjoy a profit-related bonus, generous leave and life insurance. But financial benefits are only the start of a Dyson career. Rapid professional growth, leadership development and new opportunities abound, driven by regular reviews and dynamic workshops. And with a vibrant culture, flexible working hours, the latest devices and a relaxed dress code reflecting our engineering spirit, it’s an exciting team environment geared to creativity, innovation and ambition.
At Dyson, it's about more than our machines. We recognise that our success comes from our inventive people. We believe in including everybody and supporting you on your journey with us
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.