Find a job 
Featured Companies 
Featured Universities 
For Companies At a Glance
- Tasks: Lead data science projects from start to finish, creating impactful machine learning models.
- Company: A cutting-edge organisation specialising in AI-driven customer engagement.
- Benefits: Remote work, competitive salary, and opportunities for professional growth.
- Other info: Join a team that values innovation and offers mentorship opportunities.
- Why this job: Make a real difference with your data skills in a dynamic, client-focused environment.
- Qualifications: Strong experience in data science, Python or R proficiency, and cloud platform knowledge.
The predicted salary is between 70000 - 90000 £ per year.
The Company
They are a specialist organisation working at the forefront of AI-driven customer engagement. Their focus is on enabling highly personalised, real-time decisions across digital channels using advanced analytics and machine learning.
The Role and Deliverables
- You will take ownership of end-to-end data science delivery, from problem definition through to deployment in live environments.
- Design, build, and deploy machine learning models within Pega-based decisioning platforms.
- Lead model development across feature engineering, training, validation, and ongoing performance monitoring.
- Develop statistical and machine learning models for personalisation, propensity scoring, and next-best-action use cases.
- Design and run experiments, including A/B testing, to quantify business impact.
- Provide technical leadership and mentoring to other data scientists, while engaging confidently with client stakeholders.
Your Skills and Experience
- Strong experience delivering data science solutions in client-facing or consulting environments.
- Advanced capability in Python and or R, with hands-on use of modern machine learning libraries.
- Experience deploying and operating models on cloud platforms such as AWS, GCP, or Azure.
- Experience with Pega Customer Decision Hub and Adaptive Decision Manager in production environments is highly desirable.
- Familiarity with MLOps practices and model monitoring frameworks is beneficial.
How to Apply
If you are looking for a senior data science role where you can combine technical depth with real client impact, apply now to learn more.
Lead Data Scientist - Full Time employer: Harnham - Data & Analytics Recruitment
Contact Detail:
Harnham - Data & Analytics Recruitment Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Lead Data Scientist - Full Time
✨Tip Number 1
Network like a pro! Reach out to your connections in the data science field and let them know you're on the lookout for opportunities. You never know who might have a lead or can refer you to a hiring manager.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your machine learning projects, especially those involving Python or R. This will give potential employers a taste of what you can do and set you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and problem-solving skills. Be ready to discuss your experience with deploying models on cloud platforms like AWS or GCP, as well as your familiarity with MLOps practices.
✨Tip Number 4
Don't forget to apply through our website! We love seeing candidates who are genuinely interested in joining our team. Plus, it makes it easier for us to keep track of your application and get back to you quickly.
We think you need these skills to ace Lead Data Scientist - Full Time
Some tips for your application 🫡
Show Off Your Skills: Make sure to highlight your experience with Python, R, and any machine learning libraries you've used. We want to see how your skills align with the role, so don’t hold back!
Tailor Your Application: Customise your CV and cover letter to reflect the specific requirements of the Lead Data Scientist position. Mention your experience in client-facing roles and any relevant projects that showcase your expertise.
Be Clear and Concise: Keep your application straightforward and to the point. We appreciate clarity, so avoid jargon unless it’s necessary to demonstrate your knowledge. Make it easy for us to see why you’re a great fit!
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it shows you’re keen on joining our team!
How to prepare for a job interview at Harnham - Data & Analytics Recruitment
✨Know Your Stuff
Make sure you brush up on your data science fundamentals, especially around machine learning models and their deployment. Be ready to discuss your experience with Python or R, and any specific projects where you've used these skills.
✨Showcase Your Leadership Skills
Since this role involves mentoring other data scientists, think of examples where you've led a project or guided a team. Prepare to share how you’ve engaged with stakeholders and the impact of your leadership on project outcomes.
✨Get Familiar with Pega
If you have experience with Pega Customer Decision Hub or Adaptive Decision Manager, be sure to highlight it. If not, do some research on how these platforms work and be prepared to discuss how you would approach using them in your role.
✨Prepare for Technical Questions
Expect technical questions that test your understanding of MLOps practices and model monitoring frameworks. Brush up on A/B testing methodologies and be ready to explain how you would quantify business impact through experiments.