Associate Data Scientist

at  Nominet

INTERPERSONAL SKILLS

• Able to take ownership of a problem and work independently to find a solution, with support from senior team members.
• Good cooperation with colleagues across the wider business to understand the problems they are trying to solve and keep them informed of progress.
• Able to explain data science models and concepts to different audiences

PROFESSIONAL SKILLS, BACKGROUND AND PROFILE

• Degree in Data Science, Machine Learning, Statistics, Maths, Physics or related subject, or relevant vocational experience
• Some experience of developing machine learning models (e.g. supervised, unsupervised, semi-supervised, deep learning, etc.), from collecting, cleaning, and understanding the data to building models and assessing accuracy.
• Experience using Python (ideally, or similar language like R) to work with data and build machine learning models.
• Experience of any other tools or languages listed above is beneficial.
• Any experience working with large quantities of data and developing efficient algorithms for machine learning is also beneficial.
• Understanding of the fundamental statistics involved in data science and wider data analysis.
• Enthusiasm to learn and keep abreast of the latest trends in data science, and able to use this knowledge to generate ideas and find the most appropriate approach to a problem.

OF ROLE

The Data Science function sits in the Insights team at Nominet and works with the wider business to develop new machine learning models that add value to the company.

Examples of some upcoming projects for our team include:

• Understanding how domains and the domain-name-system (DNS) are used,
• Detecting abuse within the .UK domain registry, and
• Predicting retention of domain registrations.

The Associate Data Scientist will focus on one project and follow it through from problem statement to completion with support from senior team members. For example, typical tasks will include:

• Contributing to workshops to understand the business problems and determine the requirements,
• “Test and learn” to understand the data and assess the feasibility of alternative solutions,
• Contributing to planning the project, including timescale estimates,
• Data cleaning,
• Specifying any necessary data requirements for the engineer’s data pipeline
• Model development, including variable development,
• Validation of the model including accuracy assessment,
• Code and analytical reviews,
• Preparing code to deploy model in ML pipeline,
• Communicating progress and resulting models with the business,
• Working with the business to use the developed model, and
• Monitoring of maintenance of models, including further development when necessary.

The Associate Data Scientist will use the following tools/languages when developing ML models: Python, Databricks platform, MLFlow model registry, various Python ML libraries (e.g. scikit-learn, TensorFlow), PySpark for distributed processing, Git for version control, SQL for ad-hoc queries. This role will give the opportunity to upskill while contributing valuable insights and new tools to the business.

JOB RESPONSIBILITIES

• Develop machine learning models that add value to the business.
• Maintain data science models including monitoring and model development.
• Work with engineers to implement new models in the production environment, and maintain and develop the code base for the ML pipeline (Python).
• Solve hard data problems (possibly without machine learning!)
• Given the opportunity to attend workshops and conferences (data science or registry business), and contribute to the wider understanding of data science & AI at Nominet
• Other business-as-usual activities like keeping documentation relevant and providing analytical or technical reviews to colleagues.