At a Glance
- Tasks: Transform complex marketing challenges into actionable AI strategies and data-driven solutions.
- Company: Join a leading consultancy in London with a focus on innovation and collaboration.
- Benefits: Enjoy competitive salary, health insurance, stock options, and exciting perks like free lunches.
- Other info: Dynamic hybrid work environment with opportunities for professional development and career growth.
- Why this job: Shape the future of AI in marketing while making a real impact on business growth.
- Qualifications: Degree in a quantitative field and experience in data science or technical consulting.
The predicted salary is between 80000 - 100000 £ per year.
We're looking for a
Senior Data Analytics & AI Consultant to join our team in London, UK, in a hybrid working mode.
In this role, you will operate at the intersection of business strategy, advanced analytics and AI, with a strong focus on commercial use cases.
You will help clients address complex marketing and sales challenges, such as customer acquisition and retention, pricing optimization, segmentation, incrementality measurement, next-best-action recommendations and marketing mix modeling, by designing and implementing data-driven solutions that deliver measurable business value.
As a trusted advisor and analytics translator, you will combine strategic consulting with hands‑on expertise, guiding organizations through AI adoption, shaping value-focused roadmaps and overseeing the delivery of advanced models and Gen AI capabilities.
This role also involves collaborating on solution design, supporting pre‑sales initiatives and ensuring a human‑centric approach to AI that aligns with regulatory and ethical standards.
If you enjoy converting complexity into clarity, influencing C‑level decisions and leveraging cutting‑edge AI tools for tangible business impact, this opportunity offers a chance to shape how enterprises use data and AI to drive growth.
Responsibilities
- Translate complex business challenges into actionable data science and AI strategies
- Shape and support high‑value opportunities, including pre‑sales activities such as proposals and technical demos
- Design, develop and deploy predictive models, forecasting systems and Gen AI‑based solutions using frameworks like LLMs and RAG architectures
- Act as a liaison between business stakeholders and engineering teams to ensure solution alignment
- Apply advanced analytical techniques (predictive modeling, time‑series forecasting, optimization) to generate tangible business results
- Promote responsible AI practices in line with ethical and regulatory standards (e. g., EU AI Act)
- Prepare clear documentation and client‑facing deliverables for analytics engagements
- Lead collaborative workshops and requirement‑gathering sessions
- Support delivery teams with technical problem‑solving and ensure project success
- Stay updated with trends and emerging technologies in AI and analytics
Requirements
- Bachelor’s or Master’s degree in a quantitative discipline such as Computer Science, Data Science, Statistics or Mathematics
- Proven experience in technical consulting or client‑facing data science roles with strong stakeholder engagement skills
- Proficiency in Python and SQL; familiarity with R is advantageous
- Practical experience in building statistical models or predictive algorithms
- Hands‑on exposure to contemporary AI concepts and Gen AI frameworks (e. g., Lang Chain, Hugging Face) and cloud‑native AI services (AWS, Azure or GCP)
- Knowledge of MLOps practices and tools like Databricks or MLflow
- Ability to tackle ambiguous problems with structured, analytical approaches
- Strong verbal and written communication skills for technical and executive audiences
- Experience in hybrid consulting environments, balancing multiple priorities
- Professional‑level English proficiency
- Nice to have
- Expertise in specialized analytics domains such as econometrics or marketing mix modeling
- Cloud or machine learning certifications
- Familiarity with containerization platforms like Docker or Kubernetes
- We offer
- EPAM Employee Stock Purchase Plan (ESPP)
- Protection benefits including life assurance, income protection and critical illness cover
- Private medical insurance and dental care
- Employee Assistance Program
- Competitive group pension plan
- Cyclescheme, Techscheme and season ticket loans
- Various perks such as free Wednesday lunch in‑office, on‑site massages and regular social events
- Learning and development opportunities including in‑house training and coaching, professional certifications, and courses
- If otherwise eligible, participation in the discretionary annual bonus program
- If otherwise eligible and hired into a qualifying level, participation in the discretionary Long‑Term Incentive (LTI) Program
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Data Analytics & AI Consultant - Marketing Expert employer: EPAM Systems
EPAM Systems is an exceptional employer, offering a dynamic work culture that fosters innovation and collaboration in the rapidly evolving field of AI. With a strong focus on employee growth, you will have access to extensive learning opportunities and benefits such as stock purchase plans, all while working remotely or in a hybrid model across Europe. Join us to make a meaningful impact in the energy and utilities sector, driving transformation strategies alongside industry leaders.
StudySmarter Expert Advice🤫
We think this is how you could land Data Analytics & AI Consultant - Marketing Expert
✨Get Involved in Data Science Meetups
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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 EPAM Systems.
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We think you need these skills to ace Data Analytics & AI Consultant - Marketing Expert
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 EPAM Systems, 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 EPAM Systems. 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 EPAM Systems
✨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 EPAM Systems!
✨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.
