At a Glance
- Tasks: Lead innovative Data Science projects that make a real-world impact.
- Company: High-growth consultancy expanding its AI & Digital capabilities.
- Benefits: Competitive salary, 25% bonus, and fully expensed travel.
- Other info: Frequent travel across the UK with excellent career growth opportunities.
- Why this job: Shape the future of AI while collaborating with top industry partners.
- Qualifications: 5+ years in Data Science/ML and consultancy experience required.
The predicted salary is between 85000 - 130000 £ per year.
A high‑growth consultancy is expanding its AI & Digital capability, hiring multiple Data Science and Machine Learning leaders at Lead level. This team solves complex, real‑world problems across Consumer, Public Sector and Defence, working closely with major AI partners.
What You’ll Do
- Lead end‑to‑end delivery of DS/ML/AI solutions with measurable commercial or operational impact
- Shape, design and implement complex client programmes
- Influence senior stakeholders and guide client decision‑making
- Coach and support junior consultants as the capability scales
- Collaborate with internal technology and consulting teams across multiple sectors
Role Requirements
- 5+ years’ experience in Data Science / Machine Learning
- Experience working in a consultancy or professional services environment (essential)
- Proven track record delivering real‑world, outcome‑driven projects (KPIs, ROI, efficiency, growth etc.)
- Ability to engage senior stakeholders and operate in ambiguous client environments
- Strong problem‑solving skills and intellectual curiosity
Travel Expectations
- Frequent UK client travel – typically 2–3 days per week on-site (London, Manchester, Edinburgh etc.)
- Some projects (e.g., Defence or secure Public Sector) may require full‑time on‑site work
- All travel fully expensed
- Candidates must be comfortable with regular travel as a core part of the role
Sectors & Impact Areas
- Consumer (personalised AI, customer analytics, digital optimisation)
- Public Sector (AI to improve long‑term care, operational efficiency, citizen services)
- Defence & Infrastructure (complex system optimisation, production acceleration)
If you are keen, apply below!
Lead Data Science Consultant in Cambridge employer: Harnham
Join a leading UK-based media organisation at the forefront of digital transformation, where your role as Director of Streaming Product and Growth will be pivotal in shaping the future of their subscription services. With a strong emphasis on innovation and a collaborative work culture, you'll have access to significant growth opportunities, competitive salary packages, and a performance-based bonus structure, all while working in a dynamic environment that values data-driven decision making and customer-centric strategies.
StudySmarter Expert Advice🤫
We think this is how you could land Lead Data Science Consultant in Cambridge
✨Get Involved in Data Science Meetups
Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like Harnham!
✨Show Off Your Projects
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Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like Harnham.
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We think you need these skills to ace Lead Data Science Consultant in Cambridge
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at Harnham, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Harnham. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at Harnham
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Harnham!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
