Data Scientist

Times Higher Education; London; Hybrid; GBP 45,000 - 60,000; Full time

Job summary

A reputable data provider in London seeks a hands-on Data Scientist to support the production of key educational rankings. The role involves collaborating on data quality analyses, implementing data pipelines, and presenting insights to various stakeholders. Ideal candidates will possess strong skills in Python, SQL, and have a keen interest in data analytics within the higher education sector. This hybrid role offers flexibility with an emphasis on teamwork and innovation.

Qualifications

• Implementing data QA pipelines.
• Strong foundations in data modelling and statistics.
• Collaboration on complex analytical projects.

Responsibilities

• Support Senior Data Scientist in producing rankings and data quality analysis.
• Assist in data consultancy projects, including maintaining codebase and ETL pipelines.
• Work with Data Engineer to disseminate data project results and develop dashboards.

Skills

Python

SQL

Data visualization

Data governance

Attention to detail

Tools

Excel

AWS

Tableau

Job description

Data Scientist
HYBRID (1 - 2 days/week in the Holborn office)

Times Higher Education is the data provider underpinning university excellence worldwide. As the organization behind the influential university ranking, with nearly five decades of expertise in higher education analysis, we offer unparalleled insights into global university performance. Our data and benchmarking tools are used by prestigious universities to achieve strategic goals, and our events series foster thought leadership in higher education.

Role context

The data team at Times Higher Education handles university data to produce analyses, including rankings. All projects involve data gathering, validation, processing, and output, with this role covering all stages in collaboration with senior team members.

The data scientist will support the production of core and secondary rankings by QA on data inputs, processing survey results, and assisting other teams in understanding results.

This role suits a hands-on data scientist (or data analyst) with strong Python and SQL skills who can quickly become proficient with our systems and domain.

The ideal candidate will have a keen interest in data wrangling and analytics and be highly collaborative.

Responsibilities

1. Support Senior Data Scientist in producing rankings, including:
   • Writing and maintaining data processing codebase (Python)
   • Conducting data quality analysis and developing QA processes
   • Suggesting analyses for dissemination through various media
   • Statistical review of data to support ranking evolution
2. Assist Senior Data Scientist in data consultancy projects, including:
   • Reviewing and maintaining codebase and ETL pipelines (Python, Excel)
   • Building skills in bibliometrics analyses (Databricks, Python)
   • Collaborating with experts to develop scalable analyses for the HE sector
3. Work with Data Engineer to disseminate data project results, including:
   • Developing analyses and dashboards with the Product team
   • Providing ad-hoc insights by querying university data (SQL)

Experience

• Implementing data QA pipelines
• Working with external data sources
• Producing high-level and in-depth data analyses
• Delivering insights to diverse audiences
• Ownership of data streams/projects
• Collaborating on complex analytical projects

Essential skills

• Data modelling and statistics fundamentals
• Strong Python skills (pandas, modular code, repositories)
• GitHub data management
• Data governance and documentation
• SQL skills (joins, subqueries, CTEs)
• Data wrangling best practices
• Advanced Excel skills
• Attention to detail and debugging
• Time management
• Data visualization and presentation skills

Desirable

• AWS
• Tableau
• Higher education data knowledge
• Performance assessment frameworks
• Survey design/data quality experience
• Entity recognition / free-text matching
• Public speaking

We value individuality and diversity, fostering an inclusive environment where everyone can be authentic and contribute their perspectives.