Machine Learning Researcher working with a diverse team to integrate ML techniques into fusion technology. Collaborating with scientists and engineers to drive innovative energy solutions.
About the role
- Lead Data & AI Scientist at Causeway building ML models and data platforms for construction software. Drive insights, implement data architectures, and collaborate with product, architecture, and engineering teams.
Responsibilities
- Identify, mine and analyse the data sets to identify valuable insights.
- Identify and feedback changes to data collection and capture that may enable additional insights.
- Coordinate across teams to implement data models and monitor outcomes.
- Develop custom data models and analysis algorithms to apply to the data sets.
- Use AI-driven approaches to create scalable and innovative solutions where necessary.
- Ensure understanding and demonstrate the effectiveness and accuracy of data sources, data gathering techniques and resulting analytics.
- Develop processes and tools to monitor and analyse performance and accuracy.
- Work closely with product owners, architects and engineers to drive product development and business outcomes.
Requirements
- A Master's degree or PhD in Mathematics, Physics, Computer Science or other quantitative field.
- 5+ years' experience using data analytical languages (Python, SQL, etc.) to manipulate data and draw insights from large data sets.
- Experience with Apache Spark / PySpark.
- Experience with relational, non-relational and data lake sources.
- Strong problem-solving skills with an emphasis on product development.
- Experience working with and creating data architectures.
- Knowledge of a variety of machine learning techniques and the MLOps lifecycle including fine tuning models.
- Knowledge of advanced statistical and data mining techniques and experience with applications.
- Excellent written and verbal communication skills for coordinating across teams and communicating with senior stakeholders.
- A drive to learn and master new technologies and techniques.
- Experience with data visualisation tools, PowerBI preferred.
- Experience with a cloud provider, Azure preferred.
Benefits
- 25 days annual leave + public holidays, increasing with length of service.
- 4% matched pension.
- Income protection and life assurance.
- Access to our award-winning benefits platform.
- Dedicated EAP available 24/7 for mental health support.
- £100 allowance towards a fitness club.
- Dell discounts.
- Private Medical Insurance.
- Paid study leave and volunteering days.
- Car Scheme.
- Hybrid working and opportunity to work from modern, collaborative offices.
- Emphasis on work-life balance.
Job title
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