Lead Data Scientist

A lead data scientist is a leader of data science, quite often with responsibility for managing and developing teams., * identify opportunities to develop statistical insight, reports and models to support organisational objectives, while collaborating across the organisation effectively

• critique statistical analyses

• use a variety of data analytics techniques (such as data mining and prescriptive and predictive analytics) for complex data analysis through the whole data life cycle

• use model outputs to produce evidence and help design services and policies

• understand a broad range of statistical tools, particularly those deployed within the organisation, and can use these appropriately and help others to use them

Data Engineering (Level Expert)

• help to identify the data engineering requirements for any data science product, while working with data engineers and data scientists to design and deliver those products into the organisation effectively

• understand the need to cleanse and prepare data before including it in data science products and can put reusable processes and checks in place

• understand a broad range of architectures, including cloud and on-premise, and data manipulation and transformation tools deployed within the organisation, and can use these tools appropriately and help others use them

Data Science Innovation (Expert)

• be a leader in the data science space

• demonstrate in-depth knowledge of data science tools and techniques, which you can use to solve problems creatively and to create opportunities for your team

• act as a coach, inspiring curiosity and creativity in others

• demonstrate in-depth knowledge of your chosen profession and keep up to date with changes in the industry

• challenge the status quo and always look for ways to improve data science

• One example of such work is proven experience to build Recurrent Neural Network (either in R or Python) from underlying data sets (after performing EDA)

Delivering business impact (Level Practitioner)

• lead and support your organisation area by using data science to create change

• identify opportunities to develop data science products to support organisational objectives, while collaborating across the organisation to fulfil goals

• show an understanding of the role of user research, and can design and manage processes to gather and establish user needs

• communicate relevant and compelling stories effectively and present analysis and data visualisations clearly to get across complex messages

• work with colleagues to implement scalable data science products, and to understand maintenance requirements

Ethics and Privacy (Level Expert)

• show an understanding of how ethical issues fit into a wider context and can work with relevant stakeholders

• stay up to date with developments in data ethics standards and legislation frameworks, using these to improve processes in your work area

• identify and respond to ethical concerns in your area of responsibility

Programming for Data Science (Level Expert)

• write complex programs and scripts

• seek to make code open source where appropriate

• supervise Junior Analysts and set coding standards for your team

• understand software architecture and how to write efficient, optimised code

• perform user testing on products prior to launch

Product Delivery (Level Expert)

• understand the differences between delivery methods, such as Agile and waterfall, and can set out how your team should use and adapt these methods

• lead a team through the different phases of the product delivery life cycle

• collaborate with the product manager to influence the direction of work

• identify and involve relevant teams to smoothly deliver data science products into the organisation, ensuring these products inform decision making

• ensure products are monitored, maintained and continually improved, engaging and working with others where necessary

• have oversight of any data science features implemented within products or services

• have a broad knowledge of data science techniques, use cases and potential impact, as well as the tools and technologies

• have extensive experience in scoping, designing and delivering data science outputs and products

• work collaboratively with a range of experts in support of organisational objectives

• communicate effectively and challenge delivery plans and priorities

• appreciate and understand data ethics, data preparation and manipulation

• appreciate and understand delivery methods, and how to deliver supported solutions at scale, * Government Digital Service (GDS): Familiarity with GDS service standards and the Technology Code of Practice.

These skills reflect the need for both technical depth and the ability to navigate the unique demands of the UK public sector environment.

Desired Qualifications

• Certifications in Azure, Databricks, or related technologies.

• Experience with public sector data initiatives and compliance requirements.

• Proven expertise and experience with machine learning and artificial intelligence concepts