Hybrid AI & Data Science Consultant β€” GenAI Leader

Hybrid AI & Data Science Consultant β€” GenAI Leader

Full-Time 80000 - 100000 Β£ / year (est.) Home office (partial)
EPAM Systems

At a Glance

  • Tasks: Design and deliver innovative Generative AI solutions and multi-agent systems.
  • Company: Join EPAM Systems, a leader in tech innovation based in London.
  • Benefits: Enjoy a hybrid work model, competitive salary, and opportunities for professional growth.
  • Other info: Be part of a dynamic team driving the future of AI.
  • Why this job: Make a real impact in the AI field with cutting-edge technology.
  • Qualifications: 6+ years in AI/ML, strong Python skills, and Azure familiarity required.

The predicted salary is between 80000 - 100000 Β£ per year.

EPAM Systems in London is seeking a Senior AI Engineer & Data Science Consultant to join their Data & AI Practice. This role involves designing and delivering Generative AI and multi-agent systems, requiring hands-on engineering leadership and technical consulting expertise.

The ideal candidate has over 6 years of experience in AI/ML, strong Python skills, and familiarity with Azure and orchestration frameworks. This hybrid position offers an opportunity to create impactful AI solutions.

Hybrid AI & Data Science Consultant β€” GenAI Leader employer: EPAM Systems

EPAM Systems is an exceptional employer that fosters a dynamic and innovative work culture in the heart of London. With a strong emphasis on employee growth, we offer extensive training and development opportunities, enabling our team to stay at the forefront of AI and data science advancements. Our hybrid work model promotes flexibility while collaborating with talented professionals, making it a rewarding environment for those looking to make a significant impact in the tech industry.

EPAM Systems

Contact Details:

EPAM Systems Recruitment Team

StudySmarter Expert Advice🀫

We think this is how you could land Hybrid AI & Data Science Consultant β€” GenAI Leader

✨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 EPAM Systems!

✨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 Hybrid AI & Data Science Consultant β€” GenAI Leader at EPAM Systems.

✨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 EPAM Systems.

✨Apply Directly through Our Website

When you find a suitable opening like Hybrid AI & Data Science Consultant β€” GenAI Leader at EPAM Systems, 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 Hybrid AI & Data Science Consultant β€” GenAI Leader

Generative AI
Multi-Agent Systems
Hands-On Engineering Leadership
Technical Consulting Expertise
AI/ML
Python
Azure

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.