Data Scientist

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

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