Data Scientist

The Data Gals | by AI Connect; City of Edinburgh; Hybrid; GBP 27,000 - 33,000; Full time

Job summary

A progressive data consultancy in Edinburgh is seeking a Graduate Data Scientist to join their dynamic team. This role offers the opportunity to engage with clients while applying analytical and programming skills in real-world scenarios. Ideal candidates will hold a strong degree in a numerate discipline and have hands-on experience with data projects. The position emphasizes mentorship and diverse exposure across the data science lifecycle in a hybrid work setting. Competitive salary up to £30,000 is offered.

Qualifications

• Strong academic grounding and hands-on exposure to data analysis.
• Experience with programming (Python, SQL, R).
• Completed at least one substantial data project.

Responsibilities

• Work on diverse data science projects across sectors.
• Collaborate with stakeholders to define data solutions.
• Analyze data to uncover actionable insights.
• Design analytical solutions including dashboards and reports.
• Engage with stakeholders to monitor impact of solutions.
• Progress towards owning projects end-to-end.

Skills

Data analysis

Problem-solving

Data visualisation

Communication skills

Python

SQL

R

Education

First-class degree in Mathematics, Statistics, or Data Science

Tools

Excel

Power BI

Tableau

Job description

Graduate Data Scientist - Edinburgh (hybrid)

Up to £30,000

The Data Gals are looking for a bright, curious graduate data scientist at the start of their career. This role is ideal for someone who doesn’t want to sit behind the scenes coding in isolation, but instead wants to work closely with clients and stakeholders, translating complex analysis into clear, practical insights that support commercial decision making.

You’ll be supported through structured training, mentoring, and hands‑on project work, giving you exposure across the full data science lifecycle — from dashboards and insight generation through to statistical modelling and machine learning.

What you’ll be doing

• Working on a wide range of data science projects across different sectors, gaining broad exposure early in your career
• Collaborating with business and client stakeholders to understand their challenges and define how data can help
• Exploring, analysing, and interpreting data to uncover patterns, trends, and actionable insightsDesigning analytical solutions that may include insight deep dives, dashboards, reports, or predictive models
• Building and delivering data driven outputs, then clearly presenting findings in a way that non-technical audiences can understand
• Continuing to engage with stakeholders after delivery to track impact and refine solutions
• Gradually progressing towards owning projects end‑to‑end, from initial scoping through to delivery

What we’re looking for

• Genuinely passionate about data, problem solving, and continuous learning
• Comfortable explaining technical ideas in simple, business‑friendly language
• Motivated, proactive, and driven to do high quality work
• Confident engaging with people and open to client facing responsibilities
• Curious and inquisitive — you ask why, not just how
• Happy working independently or as part of a collaborative team

Technical foundations

You don’t need to be an expert yet, but you should have a strong academic grounding and hands‑on exposure to:

• Data analysis and trend identification
• Programming experience from your degree or projects (e.g. Python, SQL, or R)
• Data visualisation and reporting (Excel, Power BI, Tableau or similar tools)
• Core statistical concepts such as regression, classification, hypothesis testing, and confidence intervals

You should have completed at least one substantial project (academic or otherwise) where you worked with data, derived insights or models, and presented your findings.

Qualifications

• A first‑class (or strong upper second) degree in a numerate subject such as Mathematics, Statistics, Data Science, or a related scientific discipline

Why this role?

• Broad exposure across insight, visualisation, analytics, and machine learning — not boxed into one area
• Strong emphasis on learning, development, and mentorship
• Real client interaction and commercial context from day one
• A clear pathway to grow into a well rounded data scientist

Visa sponsorship is NOT available for candidates

Apply today or send your CV to [e-mail]