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- Tasks: Lead data science projects, from problem definition to model deployment.
- Company: Specialist tech consultancy focused on advanced data science solutions.
- Benefits: Competitive salary, hybrid work model, and a focus on professional growth.
- Why this job: Make a real impact with cutting-edge data science in mission-critical environments.
- Qualifications: Strong Python and SQL skills, experience with deep learning frameworks.
- Other info: Join a high-calibre team valuing autonomy and technical excellence.
The predicted salary is between 48000 - 64000 £ per year.
Hybrid - 1/2 days a week in Guildford
Up to £80,000
About the Role
Our client is a specialist technology and analytics consultancy delivering advanced data science solutions into complex, mission-critical environments. Working across sectors such as aviation, defence and high-reliability systems, they help organisations turn challenging, data-rich problems into scalable, impactful solutions.
They are now looking for a Senior Data Scientist to take a leading role across a portfolio of technically demanding projects. You’ll operate end-to-end - shaping problem definitions, engineering data pipelines, developing advanced models, and ensuring outputs are robust, explainable and deployable in real-world settings.
This is a hands-on role for someone who enjoys technical depth, variety, and ownership, and who is comfortable applying the right techniques to each problem - from statistical analysis through to machine learning and deep learning models.
You’ll join a small, high-calibre team that values autonomy, flexibility and technical excellence. The environment combines the rigour of mission-critical work with a modern, product-led mindset — giving you the opportunity to build scalable solutions, launch new capabilities, and see your work make a tangible impact.
Key Responsibilities
- Translating complex, ambiguous problem statements into clear, actionable data science solutions.
- Owning the full data science lifecycle, from data ingestion and feature engineering through to modelling, evaluation and deployment.
- Developing statistical, machine learning and deep learning models to support high-impact, real-world decision making.
- Working with large, structured and unstructured datasets, combining and enriching multiple data sources.
- Collaborating closely with other data scientists, engineers and stakeholders to deliver production-ready solutions.
Your work will focus on delivering high-value outcomes, including:
- Advanced statistical and probabilistic modelling.
- Machine learning and deep learning model development.
- Building scalable, maintainable analytical pipelines.
- Delivering insight and models that perform reliably in complex operational environments.
What We’re Looking For
- Strong experience in Python and SQL, including libraries such as Pandas, NumPy and scikit-learn.
- Experience working with deep learning frameworks such as PyTorch or TensorFlow.
- A solid grounding in statistics and probability, with strong mathematical foundations (calculus and linear algebra highly advantageous).
- Experience working across the full data science project lifecycle.
- A pragmatic, engineering-minded approach to data science, with a focus on real-world impact.
- Strong communication skills and the ability to work collaboratively in technical, cross-functional teams.
If this role looks of interest, please apply below.
Please note - this role cannot offer sponsorship.
Senior Data Scientist employer: Harnham
Contact Detail:
Harnham Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Data Scientist
✨Tip Number 1
Network like a pro! Reach out to your connections in the data science field, attend meetups, and engage in online forums. You never know who might have a lead on that perfect Senior Data Scientist role.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving Python, SQL, and machine learning. This will give potential employers a taste of what you can do and how you tackle complex problems.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and problem-solving skills. Be ready to discuss your experience with data pipelines and model development, as well as how you've collaborated with teams to deliver impactful solutions.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who are proactive about their job search!
We think you need these skills to ace Senior Data Scientist
Some tips for your application 🫡
Tailor Your CV: Make sure your CV reflects the skills and experiences that match the Senior Data Scientist role. Highlight your experience with Python, SQL, and any deep learning frameworks you've used. We want to see how you can bring value to our team!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about data science and how your background aligns with our mission at StudySmarter. Be sure to mention specific projects or achievements that demonstrate your expertise.
Showcase Your Problem-Solving Skills: In your application, give examples of how you've tackled complex data problems in the past. We love seeing candidates who can translate ambiguous challenges into clear, actionable solutions. This will show us your thought process and technical depth!
Apply Through Our Website: We encourage you to apply directly through our website for the best chance of getting noticed. It’s super easy, and you’ll be able to keep track of your application status. Plus, we love seeing applications come through our own channels!
How to prepare for a job interview at Harnham
✨Know Your Data Science Fundamentals
Brush up on your statistics, probability, and mathematical foundations. Be ready to discuss how these concepts apply to real-world problems, especially in the context of machine learning and deep learning models.
✨Showcase Your Technical Skills
Prepare to demonstrate your proficiency in Python and SQL. Have examples ready that highlight your experience with libraries like Pandas, NumPy, and scikit-learn, as well as any deep learning frameworks you've used, such as PyTorch or TensorFlow.
✨Understand the Full Data Science Lifecycle
Be prepared to talk about your experience across the entire data science project lifecycle. Discuss specific projects where you owned the process from data ingestion to deployment, and how you ensured the solutions were robust and scalable.
✨Communicate Effectively
Practice explaining complex technical concepts in simple terms. Since collaboration is key in this role, being able to communicate your ideas clearly to both technical and non-technical stakeholders will set you apart.
