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- Tasks: Work on diverse data science projects, translating complex analysis into actionable insights.
- Company: Join The Data Gals, a vibrant team in Edinburgh with a focus on collaboration.
- Benefits: Up to £30,000 salary, structured training, mentorship, and hands-on project experience.
- Why this job: Gain broad exposure to data science and real client interaction from day one.
- Qualifications: Strong academic background in numerate subjects and hands-on data experience.
- Other info: Exciting career growth opportunities in a supportive, dynamic environment.
The predicted salary is between 24000 - 36000 £ per year.
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 insights
- Designing 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
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.
Data Scientist in Edinburgh employer: The Data Gals | by AI Connect
Contact Detail:
The Data Gals | by AI Connect Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Scientist in Edinburgh
✨Tip Number 1
Network like a pro! Get out there and connect with people in the data science field. Attend meetups, webinars, or even local events. You never know who might have a lead on your dream job!
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those where you’ve turned data into actionable insights. This will help you stand out when chatting with potential employers.
✨Tip Number 3
Practice your pitch! Be ready to explain your projects and how you can add value to a team. Keep it simple and relatable, so even non-techies can understand your brilliance.
✨Tip Number 4
Don’t forget to apply through our website! We’re always on the lookout for passionate data enthusiasts. Plus, it’s a great way to get noticed by our hiring team directly.
We think you need these skills to ace Data Scientist in Edinburgh
Some tips for your application 🫡
Show Your Passion for Data: Let us see your enthusiasm for data in your application! Share any projects or experiences that highlight your curiosity and problem-solving skills. We love candidates who are genuinely excited about the field.
Keep It Clear and Simple: Remember, we want to see how you can explain complex ideas in a straightforward way. Use clear language and avoid jargon when describing your experiences. This will show us you can communicate effectively with non-technical audiences.
Highlight Relevant Skills: Make sure to showcase your programming experience and any tools you've used, like Python or SQL. We’re looking for a solid foundation, so don’t shy away from mentioning your hands-on exposure to data analysis and visualisation.
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way to ensure your application gets into our hands quickly. Plus, it shows us you’re proactive and keen to join our team!
How to prepare for a job interview at The Data Gals | by AI Connect
✨Know Your Data
Before the interview, brush up on your data analysis skills and be ready to discuss any projects you've worked on. Be prepared to explain how you derived insights from data and the tools you used, like Python or SQL. This shows your hands-on experience and passion for data.
✨Communicate Clearly
Since this role involves translating complex data into simple insights, practice explaining technical concepts in layman's terms. Think of examples where you've had to present findings to non-technical audiences, as this will demonstrate your ability to engage with clients effectively.
✨Show Your Curiosity
During the interview, ask insightful questions about the company's data challenges and how they approach problem-solving. This not only shows your genuine interest but also aligns with their desire for a curious candidate who asks 'why' and not just 'how'.
✨Be Ready to Collaborate
Highlight your teamwork experiences and how you've worked with others to achieve common goals. Since the role requires collaboration with stakeholders, sharing examples of successful teamwork will illustrate your ability to thrive in a client-facing environment.
