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- Tasks: Lead the design and deployment of machine learning solutions for top clients.
- Company: Join a global leader in marketing and customer experience.
- Benefits: Enjoy a hybrid work model and competitive salary with growth opportunities.
- Why this job: Make a real impact while collaborating with diverse teams in an innovative environment.
- Qualifications: 5+ years in data science, strong Python and SQL skills, AWS experience required.
- Other info: Mentorship opportunities available for aspiring data scientists.
The predicted salary is between 80000 - 120000 £ per year.
Join a high-impact data science team at a global marketing and customer experience company. As a Principal Data Scientist, you’ll lead the development of end-to-end machine learning solutions that drive business transformation across household-name clients.
You’ll partner closely with engineers, strategists, and creatives in a genuinely cross-functional setting.
As a Principal Data Scientist, you will:
- Lead the design, implementation, and deployment of advanced ML solutions across the full stack — from data engineering and modelling to cloud deployment (AWS).
- Scope and steer high-impact projects from ideation to delivery, aligning technical strategy with business objectives.
- Serve as a technical mentor to mid-level and junior data scientists.
- Represent the data science function in client conversations and cross-functional planning.
Requirements:
- 5+ years of experience building and deploying DS/ML products in production.
- Strong Python and SQL skills; deep understanding of ML lifecycle from prototyping to production.
- Hands-on experience with AWS (or similar), Git, and CI/CD pipelines.
- Ability to balance high-level strategic thinking with hands-on implementation.
- Excellent communicator, able to tailor messages for technical, creative, and client audiences.
- Experience with marketing data, customer-level modelling, or decision science (e.g. uplift, attribution, causal AI, optimization).
You’ll be hands-on where it counts, shaping projects, mentoring talent, and collaborating across disciplines to create meaningful, measurable impact.
Principal Data Scientist, AWS Marketing Science employer: Harnham
Contact Detail:
Harnham Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Principal Data Scientist, AWS Marketing Science
✨Tip Number 1
Familiarise yourself with the latest trends in machine learning and data science, especially those relevant to marketing. This will not only help you in interviews but also demonstrate your passion and commitment to the field.
✨Tip Number 2
Network with professionals in the data science community, particularly those who work in marketing. Attend industry events or webinars to connect with potential colleagues and learn about their experiences at companies like ours.
✨Tip Number 3
Prepare to discuss specific projects where you've successfully implemented machine learning solutions. 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 communication skills, especially in translating complex technical concepts into layman's terms. As a Principal Data Scientist, you'll need to effectively communicate with both technical teams and clients, so practice articulating your ideas clearly.
We think you need these skills to ace Principal Data Scientist, AWS Marketing Science
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in data science and machine learning, particularly any projects involving AWS. Emphasise your technical skills in Python and SQL, as well as your experience with the ML lifecycle.
Craft a Compelling Cover Letter: In your cover letter, explain why you are passionate about data science and how your background aligns with the role. Mention specific projects where you've led teams or mentored others, showcasing your leadership skills.
Showcase Relevant Projects: Include examples of past projects that demonstrate your ability to design and implement ML solutions. Highlight any experience with marketing data or decision science, as this is particularly relevant to the position.
Prepare for Technical Questions: Be ready to discuss your technical expertise in detail. Prepare to explain your approach to building and deploying data science products, and be prepared to answer questions about your experience with AWS and CI/CD pipelines.
How to prepare for a job interview at Harnham
✨Showcase Your Technical Expertise
Be prepared to discuss your experience with Python, SQL, and AWS in detail. Highlight specific projects where you've built and deployed machine learning solutions, and be ready to explain the ML lifecycle from prototyping to production.
✨Demonstrate Leadership Skills
As a Principal Data Scientist, you'll be expected to mentor others. Share examples of how you've guided junior data scientists or led cross-functional teams in previous roles. This will show your ability to lead and inspire.
✨Align with Business Objectives
Understand the company's goals and be ready to discuss how your technical strategies can drive business transformation. Prepare to talk about how you've scoped and steered high-impact projects that align with business needs.
✨Communicate Effectively
Since you'll be representing the data science function in client conversations, practice tailoring your communication for different audiences. Be ready to explain complex concepts in simple terms, demonstrating your excellent communication skills.
