Senior Data Scientist (Generative AI) - RELOCATION TO ABU DHABI

SoftServe
London
11 months ago
Applications closed

Related Jobs

View all jobs

Senior Data Scientist

Senior Data Scientist

Senior Data Scientist

Senior Data Engineer

Data Science Consultant

Senior RF Data Scientist / Research Engineer

Please note: this position requires relocation to Abu Dhabi for a minimum period of 12 months. Project duration: 36 months+. Softserve will support relocation of selected candidates.


WE ARE

SoftServe is a digital authority that advises and provides service at the cutting edge of technology. We empower enterprises and software companies to (re)identify their differentiation, accelerate solution development, and vigorously compete in today’s digital economy.


Transforming the way thousands of global organizations do business by developing the most innovative technologies and processes in Big Data, the Internet of Things (IoT), Data Science, and Experience Design. We are one of the largest teams in Eastern Europe that stood at the origins of data science, providing tons of experience and working with the best talents in the field.

In the Data Science Center of Excellence, we contribute to a wide range of projects in different areas, domains, and technologies. The GenAI Strategy at SoftServe aims to spearhead the development and implementation of intelligent software systems that integrate GenAI, AI, Data Analytics, MLOps, and Cloud infrastructure.


IF YOU ARE

  • A holder of a Ph.D. or master's Degree in Computer Science, or a related field
  • Experienced in Generative AI and natural language processing (NLP) techniques such as large-scale transformer models and generative pre-trained LLMs (GPT-4, Claude, Gemini, and beyond)
  • Knowledgeable of the latest developments in diffusion models and other generative frameworks for both text and image generation
  • Competent in Generative AI and language models to spearhead innovative initiatives that leverage cutting-edge techniques in NLP and AI
  • Adept at applying advanced deep learning techniques in practical scenarios
  • Well-versed in the latest advancements and trends in machine learning, deep learning, NLP, and their practical applications
  • Proficient in working with the latest pre-trained language models like GPT-4, BERT, and their subsequent iterations, including fine-tuning for specific tasks
  • Aware of the software development lifecycle of AI projects, machine learning operationalization processes
  • Experienced with AI solutions deployment to main cloud providers
  • Hands-on with Python and TensorFlow or PyTorch
  • Possessing strong interpersonal, analytical, and problem-solving skills
  • Easily translating complex concepts in clear, concise, and meaningful ways, that a non-technical audience can easily understand
  • Capable of maintaining business communication in English at the upper-intermediate level


AND YOU WANT TO

  • Work with the full stack of data analysis, deep learning, and machine learning model pipeline that includes deep analysis of customer data, modeling, and deployment in production
  • Choose relevant computational tools for study, experiment, or trial research objectives
  • Drive the development of innovative solutions for language generation, text synthesis, and creative content generation using the latest state-of-the-art techniques
  • Develop and implement advanced Generative AI solutions such as intelligent assistants, Retrieval-Augmented Generation (RAG) systems, and other innovative applications
  • Produce clear, concise, well-organized, and error-free computer programs with the appropriate technological stack
  • Present results directly to stakeholders and gather business requirements
  • Develop expertise in state-of-the-art Generative AI techniques and methodologies
  • Grow your skill set within a dynamic and supportive environment
  • Work with Big Data solutions and advanced data tools in cloud platforms
  • Build and operationalize ML models, including data manipulation, experiment design, developing analysis plans, and generating insights
  • Lead teams of data scientists and software engineers to successful project execution


TOGETHER WE WILL

  • Maintain a synergy of Data Scientists, DevOps team, and ML Engineers to build infrastructure, set up processes, productize machine learning pipelines, and integrate them into existing business environments
  • Drive innovation in the realm of Generative AI and Language Models contributing to groundbreaking projects that redefine AI-powered content generation
  • Communicate with the world-leading companies from our logos portfolio
  • Enjoy the opportunity to work with the latest modern tools and technologies on various projects
  • Participate in international events and get certifications in cutting-edge technologies
  • Have access to powerful educational and mentorship programs
  • Revolutionize the software industry and drive innovation in adaptive self-learning technologies by leveraging multidisciplinary expertise!


All qualified applicants will receive consideration for employment without regard to race, color, religion, age, sex, national origin, disability, sexual orientation, gender identity/expression, or protected veteran status. SoftServe is an Equal Opportunity Employer.

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.

New Data Science Employers to Watch in 2026: UK and International Companies Leading Analytics and AI Innovation

Data science has emerged as one of the most transformative forces across industries, turning raw information into actionable insights, predictive models, and AI-powered solutions. In 2026, the UK is witnessing a surge in organisations where data science is not just a support function but the core of their products and services. For professionals exploring opportunities on www.DataScience-Jobs.co.uk , identifying these employers early can provide a competitive advantage in a market with high demand for advanced analytics and machine learning expertise. This article highlights new and high-growth data science employers to watch in 2026, focusing on UK startups, scale-ups, and global firms expanding their data science operations locally. All of the companies included have recently raised investment, won high-profile contracts, or significantly scaled their analytics teams.

How Many Data Science Tools Do You Need to Know to Get a Data Science Job?

If you’re trying to break into data science — or progress your career — it can feel like you are drowning in names: Python, R, TensorFlow, PyTorch, SQL, Spark, AWS, Scikit-learn, Jupyter, Tableau, Power BI…the list just keeps going. With every job advert listing a different combination of tools, many applicants fall into a trap: they try to learn everything. The result? Long tool lists that sound impressive — but little depth to back them up. Here’s the straight-talk version most hiring managers won’t explicitly tell you: 👉 You don’t need to know every data science tool to get hired. 👉 You need to know the right ones — deeply — and know how to use them to solve real problems. Tools matter, but only in service of outcomes. So how many data science tools do you actually need to know to get a job? For most job seekers, the answer is not “27” — it’s more like 8–12, thoughtfully chosen and well understood. This guide explains what employers really value, which tools are core, which are role-specific, and how to focus your toolbox so your CV and interviews shine.

What Hiring Managers Look for First in Data Science Job Applications (UK Guide)

If you’re applying for data science roles in the UK, it’s crucial to understand what hiring managers focus on before they dive into your full CV. In competitive markets, recruiters and hiring managers often make their first decisions in the first 10–20 seconds of scanning an application — and in data science, there are specific signals they look for first. Data science isn’t just about coding or statistics — it’s about producing insights, shipping models, collaborating with teams, and solving real business problems. This guide helps you understand exactly what hiring managers look for first in data science applications — and how to structure your CV, portfolio and cover letter so you leap to the top of the shortlist.