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- Tasks: Join a dynamic team to build and deploy machine learning solutions using SQL and Python.
- Company: Be part of a global marketing and customer experience company with a high-performing data team.
- Benefits: Enjoy a hybrid work model, flexible hours, and opportunities for rapid career growth.
- Why this job: Make a real impact on major client projects while working in a collaborative and fast-paced environment.
- Qualifications: Degree in STEM or equivalent experience; 1-4 years in delivering ML solutions; strong Python and SQL skills.
- Other info: This role offers diverse challenges beyond typical data science tasks, perfect for ambitious individuals.
The predicted salary is between 36000 - 60000 £ per year.
An opportunity to join a high-performing data team at a global marketing and customer experience company. You’ll work across a variety of data science challenges — from prototyping ideas to deploying full-scale ML solutions — in a fast-paced, collaborative environment. This role is ideal for someone with strong technical foundations and a generalist mindset, looking to grow quickly and make a tangible impact across major client projects.
As a Data Scientist, you will:
- Build and deploy machine learning solutions end-to-end, from SQL-based feature engineering to model development in Python and cloud deployment (AWS).
- Take ownership of workstreams within larger projects, with opportunities to lead as you grow.
Requirements:
- Degree in a STEM field or equivalent hands-on experience.
- ~1–4 years’ experience delivering ML solutions in production, ideally in fast-moving teams or startups.
- Strong Python and SQL skills; experience building and deploying models end-to-end.
- Familiarity with AWS (or similar), Git, and CI/CD pipelines.
- Experience with marketing data or customer-level models (e.g. uplift, attribution, causal inference, campaign optimization).
- Exposure to A/B testing and experimentation frameworks.
This isn’t a narrow data science role — you won’t just tune models or clean data. It’s the perfect step for someone who wants to move fast, own their growth, and help shape impactful AI solutions in a cross-disciplinary setting.
Data Scientist SQL/python employer: Harnham
Contact Detail:
Harnham Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Scientist SQL/python
✨Tip Number 1
Familiarise yourself with the latest trends in machine learning and data science, especially those relevant to marketing and customer experience. This will not only help you during interviews but also demonstrate your genuine interest in the role.
✨Tip Number 2
Network with current or former employees of StudySmarter or similar companies. Engaging with them on platforms like LinkedIn can provide you with insights into the company culture and expectations, which can be invaluable during the interview process.
✨Tip Number 3
Prepare to discuss specific projects where you've built and deployed machine learning models. Be ready to explain your thought process, the challenges you faced, and how you overcame them, as this will showcase your hands-on experience.
✨Tip Number 4
Brush up on your SQL and Python skills by working on real-world datasets. Consider contributing to open-source projects or creating your own portfolio of projects that highlight your ability to handle end-to-end ML solutions.
We think you need these skills to ace Data Scientist SQL/python
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with SQL and Python, as well as any relevant projects involving machine learning solutions. Emphasise your hands-on experience and any specific achievements in data science that align with the job description.
Craft a Compelling Cover Letter: In your cover letter, express your enthusiasm for the role and the company. Discuss how your background in STEM and your experience with AWS, Git, and CI/CD pipelines make you a strong candidate. Mention specific projects where you've built and deployed ML solutions.
Showcase Relevant Projects: If you have a portfolio or GitHub repository, include links to projects that demonstrate your skills in building and deploying machine learning models. Highlight any work related to marketing data or customer-level models, as this is particularly relevant to the role.
Prepare for Technical Questions: Anticipate technical questions related to SQL, Python, and machine learning during the interview process. Brush up on your knowledge of A/B testing and experimentation frameworks, as well as your understanding of cloud deployment processes, to showcase your expertise.
How to prepare for a job interview at Harnham
✨Showcase Your Technical Skills
Be prepared to discuss your experience with Python and SQL in detail. Bring examples of projects where you've built and deployed machine learning models, and be ready to explain your thought process and the challenges you faced.
✨Demonstrate Your Problem-Solving Ability
Expect to tackle some data science challenges during the interview. Practice explaining your approach to problem-solving, especially in relation to marketing data or customer-level models, as this will show your ability to think critically and creatively.
✨Familiarise Yourself with AWS and CI/CD
Since the role involves cloud deployment, brush up on your knowledge of AWS and CI/CD pipelines. Be ready to discuss how you've used these tools in past projects and how they can enhance the deployment of machine learning solutions.
✨Prepare Questions About the Company and Role
Show your interest in the company by preparing thoughtful questions about their data team and the specific projects you'll be working on. This not only demonstrates your enthusiasm but also helps you assess if the role aligns with your career goals.
