Data Scientist

Data Scientist role within the Data & Analytics Project Pool Team to work alongside other Data Scientists to lead and support the implementation of new cloud Data & Analytics services to business users, as well as providing support for existing on premise service offerings.
They will be working closely with the Technology delivery team who are delivering our new Enterprise Data Platform to ensure that the Data Science tooling is delivered in a way which Data Scientists will be able to enjoy using.You will be helping to develop capabilities (e.g. helper libraries) that make the platform easier to use. Similarly, you will work alongside colleagues to build analytical pipelines for both our on-prem (Cloudera) and Cloud (Azure) platform.

Responsibilities Include:
Test our new analytical cloud services and work with Technology colleagues to address user pain points.
• Support business users with scoping, on-boarding and delivery of their use cases for our on prem Data & Analytics Platform and new cloud Enterprise Data Platform.
• Lead the delivery of pipelines that ingest, store and analyse data, ensuring that data and analysis are accessible.
• Develop capabilities to support enterprise use of our Platforms.
• Upskill business users in analytical standards and data science tools and techniques.
• Build and productize pipelines.
• Develop and manage use cases.
• Conduct internal skills mapping for technologies such as R, Python, Azure, Machine Learning (ML), and Databricks.

Essential criteria and experience
Proficiency in one or more analytical tools e.g. R, Python, Tableau, Apache Spark, etc.
• Proficiency in Azure Machine Learning and Azure DataBricks.
• Pro-activity and self-starting attitude.
• Excellent analytical and problem-solving ability.
• Interest in data science techniques and understanding of how to use them to answer real-world questions.
• Knowledge and experience of how to maintain data, tools and processes to generate reproducible analysis and implement robust and valuable data solutions.
• Experience of leading data science work within a team environment.
• Strong written and verbal communication skills to engage effectively with stakeholders at a range of seniorities and knowledge levels.
• An open and collaborative approach in order to foster strong positive partnerships with colleagues all over the organisation