Director/Snr Director, Data Science Consulting - Machine Learning/Artificial Intelligence (ML/AI)

Epam
London, England
25 months ago
Applications closed

Related Jobs

View all jobs

Director of Data & AI

Robert Walters Cheshire, United Kingdom
£110,000 – £120,000 pa On-site

Director, AI Engineering

Faculty AI London, United Kingdom
Hybrid

Director, Customer Success - DACH

Synthesia London, United Kingdom
£80,000 – £120,000 pa Hybrid

Director of Security

PolyAI London, United Kingdom

Director: Forensic Technology/Data Analytics/FinCrime/Regulatory

Brimstone-Recruitment City Of Dublin, Ireland

Account Director, Startups

OpenAI London, United Kingdom
Hybrid
Posted
30 Mar 2024 (25 months ago)

Description

ABOUT THE ROLE



Are you an avid technologist who enjoys solving and driving complex Data & Analytics challenges? Are you hungry to thrive in a fast paced entrepreneurial engineering environment and take ownership for critical technical and business decisions that directly impact EPAM and our clients?

As one of the worlds leading digital transformation service providers, we are looking to aggressively expand our Data Practice across Europe to meet increasing client demand for our services. We are open to hiring people at Director or Snr Director level within the Data & Analytics/Data Science Consulting Practice with a specific focus on Machine Learning (ML) and Artificial Intelligence (AI).

The roles offer exciting opportunities to work with leading-edge technologies, deliver ML/AI driven solutions, play a highly visible leading role in the organisation whilst partnering closely with multiple clients across various industries and our Data leadership teams globally.

We offer a flexible work set-up with face to face client meetings from time to time.

Responsibilities

Provide technical leadership and strategic direction expertise in ML/AI, driving the design, development, and implementation of ML/AI solutions for clients Engage with clients to understand their business challenges and requirements, and effectively communicate how ML/AI solutions can address them Collaborate with cross-functional teams to define project scope, develop data models, and apply appropriate ML algorithms to deliver high-quality solutions Lead the identification of new ML/AI opportunities, either through selling solutions or securing funding, by leveraging your technical expertise and engaging senior decision-makers Shape data solutions and properly scope / price engagements, establishing optimal operating models and project team organisation, and leading the transition from the sales process to the delivery phase Lead the evaluation and selection of ML/AI tools, frameworks, and technologies, ensuring their alignment with business objectives and technical requirements Foster and maintain strong relationships with clients, ensuring their satisfaction through effective project delivery, clear communication, and timely issue resolution Engage client stakeholders at the executive / C-level, helping them drive enterprise-wide agenda to maximize growth Provide guidance and mentorship to junior team members, fostering their professional growth and development in ML/AI Stay updated with the latest advancements in ML/AI and emerging technologies, proactively recommending new approaches and methodologies to address challenges in the space/markets and geographies in which the clients operate Support sales / pre-sales activities by assessing Data opportunities, responding to RFPs, creating proposals and presentations

Requirements

Bachelor's or master's degree in Computer Science, Data Science, or a related field or relevant work experience Strong experience in a senior/leadership role within Data & Analytics/ML/AI Proven track record in designing and implementing ML/AI solutions Solid understanding of ML algorithms, data pre-processing, feature selection, and model evaluation techniques Demonstrated experience in engaging and influencing senior stakeholders to secure funding or sell ML/AI projects Strong communication skills, with the ability to explain complex technical concepts to both technical and non-technical audiences, capable of collaborating with cross-functional teams in different geographies and building strong client relationships Technical proficiency in programming languages such as Python, R, or Java, and ML libraries/frameworks such as TensorFlow, PyTorch, or scikit-learn Awareness of Cloud (Azure, GCP, AWS), Big Data, Analytics, and Data Science technologies and trends Confident in expressing points-of-view, making recommendations and presenting analysis and recommendations up to board level where appropriate Excellent problem-solving skills and the ability to analyse complex business requirements and translate them into practical ML/AI solutions Consulting and pre-sales experience is a plus, but not mandatory

We Offer

A competitive group pension plan and protection benefits including life assurance, income protection and critical illness cover Private medical insurance and dental care Cyclescheme, Techscheme and season ticket loans Employee assistance program Great learning and development opportunities, including in-house professional training, career advisory and coaching, sponsored professional certifications, well-being programs, LinkedIn Learning Solutions and much more EPAM Employee Stock Purchase Plan (ESPP) Various perks such as gym discounts, free Wednesday lunch in-office, on-site massages and regular social events Certain benefits and perks may be subject to eligibility requirements and may be available only after you have passed your probationary period

About EPAM

EPAM is a leading global provider of digital platform engineering and development services. We are committed to having a positive impact on our customers, our employees, and our communities. We embrace a dynamic and inclusive culture. Here you will collaborate with multi-national teams, contribute to a myriad of innovative projects that deliver the most creative and cutting-edge solutions, and have an opportunity to continuously learn and grow. No matter where you are located, you will join a dedicated, creative, and diverse community that will help you discover your fullest potential

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Where to Advertise Machine Learning Jobs in the UK (2026 Guide)

Advertising machine learning jobs in the UK requires a different approach to most technical hiring. The candidate pool is small, highly specialised and in demand across AI labs, financial services, healthcare, autonomous systems and consumer technology simultaneously. Machine learning engineers and researchers move between roles through professional networks, conference communities and specialist platforms — not general job boards where ML roles compete with unrelated software engineering positions for the same audience. This guide, published by MachineLearningJobs.co.uk, covers where to advertise machine learning roles in the UK in 2026, how the main platforms compare, what employers should expect to pay, and what the data says about hiring across different role types.

New Machine Learning Employers to Watch in 2026: UK and Global Companies Driving ML Innovation

Machine learning (ML) has transitioned from a specialised field into a core business capability. In 2026, organisations across healthcare, finance, robotics, autonomous systems, natural language processing, and analytics are expanding their machine learning teams to build scalable intelligent products and services. For professionals exploring opportunities on www.MachineLearningJobs.co.uk , understanding the companies that are scaling, winning investment, or securing high‑impact contracts is crucial. This article highlights the new and high‑growth machine learning employers to watch in 2026, focusing on UK innovators, international firms with significant UK presence, and global platforms investing in machine learning talent locally.

How Many Machine Learning Tools Do You Need to Know to Get a Machine Learning Job?

Machine learning is one of the most exciting and rapidly growing areas of tech. But for job seekers it can also feel like a maze of tools, frameworks and platforms. One job advert wants TensorFlow and Keras. Another mentions PyTorch, scikit-learn and Spark. A third lists Mlflow, Docker, Kubernetes and more. With so many names out there, it’s easy to fall into the trap of thinking you must learn everything just to be competitive. Here’s the honest truth most machine learning hiring managers won’t say out loud: 👉 They don’t hire you because you know every tool. They hire you because you can solve real problems with the tools you know. Tools are important — no doubt — but context, judgement and outcomes matter far more. So how many machine learning tools do you actually need to know to get a job? For most job seekers, the real number is far smaller than you think — and more logically grouped. This guide breaks down exactly what employers expect, which tools are core, which are role-specific, and how to structure your learning for real career results.