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For Companies At a Glance
- Tasks: Help enterprises unlock value from behavioural data using advanced AI and machine learning.
- Company: Fast-growing AI analytics company with a collaborative culture.
- Benefits: Flexible hybrid working, 26 days holiday, and strong growth opportunities.
- Why this job: Join a dynamic team and make a real impact with cutting-edge AI technology.
- Qualifications: Experience in data science, machine learning, and strong communication skills.
- Other info: Work with global clients and contribute to innovative data science solutions.
The predicted salary is between 36000 - 60000 £ per year.
A fast-growing AI analytics company is seeking a Data Science Consultant to help enterprise organisations unlock value from large-scale behavioural data using advanced machine learning and AI technologies. The company builds cutting-edge behavioural AI platforms used by global enterprises across telecoms, financial services, retail and digital industries. Their technology processes billions of customer interaction events daily, enabling organisations to better understand behaviour, personalise experiences and drive measurable commercial outcomes.
Recognised as one of Europe’s fastest-growing technology companies, the business is expanding its Client Success team and is looking for someone who combines strong data science capability with a consultative mindset. This role is ideal for data scientists looking to become more client-facing, or technical consultants with a strong machine learning background who want to work with modern AI tooling and large-scale data.
The Role
You will join the Client Success team, working closely with enterprise customers, product teams and data engineers to deliver real-world AI and data science solutions. This is a hybrid role combining technical delivery and consulting, helping customers translate behavioural data into actionable insights and measurable ROI. The position is approximately 50% technical data science and 50% client consulting.
Key Responsibilities
- Work with enterprise customers to understand complex business problems and translate them into data science solutions
- Build and prototype machine learning models to generate behavioural insights and predictive capabilities
- Leverage the company’s core data science platform to deliver measurable value to customers
- Design and engineer new features and models to improve understanding of customer behaviour
- Communicate technical concepts clearly to non-technical stakeholders including customers, sales teams and product teams
- Help customers develop an understanding of how behavioural AI models drive business outcomes
- Collaborate with product and engineering teams to identify new opportunities for data science innovation
- Contribute to the internal data science community and share best practices
Skills & Experience
- Strong ability to break down complex client problems and apply data science solutions that drive measurable business outcomes
- Experience building and evaluating machine learning models (e.g. clustering, NLP, deep learning)
- Experience with data exploration, feature engineering and model evaluation
- Familiarity with modern AI tooling and frameworks (e.g. agentic AI, MCP servers or similar AI infrastructure)
- Ability to work closely with both technical and non-technical stakeholders
- Strong communication skills with the ability to explain technical ideas in commercial terms
- Willingness to travel occasionally to meet enterprise clients (typically 1–2 short trips per quarter)
- Experience working with B2B data platforms or analytics products
- Experience with Spark SQL, PySpark or distributed data systems
- Experience with large-scale data tooling (e.g. Spark, Hive, Databricks)
- Exposure to LLMs, generative AI, agentic systems or causal AI
The Company
- High-growth AI and behavioural analytics company
- Enterprise customers across multiple industries
- Platform processes billions of behavioural data events daily
- International team with offices across Europe, the US and the Middle East
- Collaborative and fast-moving environment with strong opportunities for impact and growth
- Flexible / hybrid working
- 26 days holiday (increasing with service)
Data Science Consultant employer: Intent HQ
Contact Detail:
Intent HQ Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Science Consultant
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with potential colleagues on LinkedIn. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your data science projects, especially those that highlight your machine learning expertise. This will give you an edge when chatting with potential employers about how you can add value.
✨Tip Number 3
Prepare for interviews by practising common data science scenarios and case studies. Be ready to explain your thought process and how you approach solving complex problems, as this is key for a consultative role.
✨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, it shows you’re genuinely interested in joining our awesome team!
We think you need these skills to ace Data Science Consultant
Some tips for your application 🫡
Tailor Your CV: Make sure your CV speaks directly to the role of Data Science Consultant. Highlight your experience with machine learning, data exploration, and any client-facing roles you've had. We want to see how your skills can help us unlock value from behavioural data!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're excited about working with us and how you can contribute to our Client Success team. Be sure to mention specific projects or experiences that relate to the job description.
Showcase Your Technical Skills: Don’t hold back on showcasing your technical prowess! Mention your experience with tools like Spark SQL, PySpark, and any machine learning models you've built. We love seeing candidates who can bridge the gap between technical and non-technical stakeholders.
Apply Through Our Website: We encourage you to apply through our website for the best chance of getting noticed. It’s the easiest way for us to keep track of your application and ensure it reaches the right people. Plus, we love seeing candidates who take that extra step!
How to prepare for a job interview at Intent HQ
✨Know Your Data Science Stuff
Make sure you brush up on your machine learning models and data science techniques. Be ready to discuss your experience with clustering, NLP, and deep learning, as well as how you've applied these in real-world scenarios. The more specific examples you can provide, the better!
✨Understand the Business Side
Since this role is about translating complex business problems into data science solutions, it’s crucial to understand the commercial impact of your work. Think about how your previous projects have driven measurable outcomes and be prepared to explain these in simple terms.
✨Communicate Like a Pro
You’ll need to explain technical concepts to non-technical stakeholders, so practice simplifying your language. Use analogies or relatable examples to make your points clear. This will show that you can bridge the gap between tech and business effectively.
✨Show Your Collaborative Spirit
This role involves working closely with clients and various teams, so highlight your teamwork skills. Share examples of how you’ve collaborated with product teams or engineers in the past, and express your enthusiasm for contributing to a community of data science professionals.