At a Glance
- Tasks: Design and deploy innovative AI solutions for leading brands, enhancing customer experiences.
- Company: Join a top global consultancy with a focus on Data Science and AI.
- Benefits: Competitive salary, bonuses, hybrid work, and excellent benefits.
- Other info: Collaborative environment with opportunities for rapid career growth.
- Why this job: Work on cutting-edge projects that make a real impact in the AI space.
- Qualifications: 2-4 years of Data Science experience and strong Python skills required.
The predicted salary is between 63000 - 77000 £ per year.
London (Hybrid) Competitive Salary + Bonus + Excellent Benefits
You must have full working rights to be considered for this opportunity.
Looking to take the next step in your Data Science consulting career? We're working with a leading global consultancy that is growing its Customer Data & AI practice. This is an exciting opportunity for a Data Scientist with around 2-4 years of experience to work on cutting-edge projects across Generative AI, customer analytics, personalisation, and digital transformation. You'll help leading brands unlock the value of their customer data, delivering AI and data science solutions that drive better customer experiences and measurable commercial outcomes.
What You'll Be Doing
- Designing, developing, and deploying Generative AI solutions for customer, marketing, CRM, and digital use cases
- Working with Large Language Models (LLMs) to build and evaluate AI-powered products and solutions
- Owning projects across the full data science lifecycle - from problem definition and solution design through to model development, deployment, testing, and business adoption
- Applying advanced analytics to customer behaviour, personalisation, marketing performance, and digital journey optimisation
- Building predictive, classification, forecasting, and recommendation models that drive commercial decision-making
- Collaborating with multidisciplinary teams and client stakeholders to solve complex business challenges
- Translating technical outputs into actionable business recommendations
What We're Looking For
- Around 2-4 years of commercial Data Science experience
- Strong Python programming skills
- Experience using GitHub and software engineering best practices
- Practical experience applying Generative AI and LLMs to real-world customer, marketing, digital, CRM, or commercial challenges
- Hands-on experience building, evaluating, and deploying Machine Learning models in production environments
- Proven end-to-end ownership of Data Science or GenAI projects - from identifying opportunities and shaping solutions through to model development, deployment, implementation, and value delivery
- Experience working with customer, marketing, CRM, web, digital, or product datasets
- Strong communication skills and an interest in client-facing consulting work
Why Apply?
- Work with globally recognised brands on high-impact AI and analytics projects
- Gain exposure to cutting-edge GenAI, LLM, and customer data initiatives
- Accelerate your consulting career within a growing Data & AI practice
- Join a collaborative team that values innovation, learning, and continuous development
Interested? Apply now or get in touch for a confidential discussion.
Consultant/Senior Consultant- Data Science & AI- customer centric in London employer: Datatech Analytics
Datatech Analytics is an exceptional employer located in the vibrant City of London, offering a dynamic work culture that fosters collaboration and innovation. As a Trading Operations Graduate Analyst, you will benefit from comprehensive training and mentorship, ensuring your professional growth while working alongside industry experts in a fast-paced environment. With a commitment to employee well-being and a focus on meaningful contributions to global trading operations, Datatech Analytics provides a rewarding career path for ambitious graduates.
StudySmarter Expert Advice🤫
We think this is how you could land Consultant/Senior Consultant- Data Science & AI- customer centric in London
✨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 Datatech Analytics!
✨Show Off Your Projects
Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like Consultant/Senior Consultant- Data Science & AI- customer centric at Datatech Analytics.
✨Leverage Professional Networks
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 Datatech Analytics.
✨Apply Directly through Our Website
When you find a suitable opening like Consultant/Senior Consultant- Data Science & AI- customer centric at Datatech Analytics, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!
We think you need these skills to ace Consultant/Senior Consultant- Data Science & AI- customer centric in London
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 Datatech Analytics, 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 Datatech Analytics. 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 Datatech Analytics
✨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 Datatech Analytics!
✨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.
