Data Scientist - Gen AI + Recommender Systems

Soho
2 months ago
Applications closed

Related Jobs

View all jobs

Data Scientist

Data Scientist - Remote

Data Scientist/Statistician

Data Scientist - Gen AI - Remote

Data Scientist - Gen AI - Remote

Data Scientist - Gen AI - Remote

Are you an experienced Data Scientist looking for a role leveraging GenAI tech?

Have you honed your skills in machine learning and kept a close eye on the transformative potential of generative AI?

Imagine a role where your expertise can drive significant change and help shape the future of an industry...

We are hiring for a Senior Data Scientist role with a focus on generative AI and recommender systems for a pioneering businesses in online search comparison.

This is your chance to work on cutting-edge projects, collaborate with brilliant minds, and see your work directly impact millions of daily users worldwide.

You'll be part of a team that's building a new online experience to inspire users with new ideas, leveraging technologies like GenAI and recommender systems to optimize image, video and text content and create a limprove the eading platform in their field.

Technical Requirements:

Interest in Generative AI and Recommender Systems: Proven experience in developing and implementing recommender system solutions and you'll be exploring Generative AI offerings. This includes Image and Video Content.

Strong Programming Skills: Proficiency in Python and SQL.

Hands-on Experience with LLMs: Practical knowledge of working with large language models (LLMs) and retrieval-augmented generation (RAG).

Advanced Evaluation Techniques: Expertise in A/B testing, human-in-the-loop evaluation, and GenAI quality metrics, ensuring the quality, relevance, and user engagement of AI-generated content.

This London-based hybrid role offers a base salary of £90-95k, plus bonuses and a host of other benefits.

Apply now for immediate consideration

Get the latest insights and jobs direct. Sign up for our newsletter.

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

Industry Insights

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

Portfolio Projects That Get You Hired for Data Science Jobs (With Real GitHub Examples)

Data science is at the forefront of innovation, enabling organisations to turn vast amounts of data into actionable insights. Whether it’s building predictive models, performing exploratory analyses, or designing end-to-end machine learning solutions, data scientists are in high demand across every sector. But how can you stand out in a crowded job market? Alongside a solid CV, a well-curated data science portfolio often makes the difference between getting an interview and getting overlooked. In this comprehensive guide, we’ll explore: Why a data science portfolio is essential for job seekers. Selecting projects that align with your target data science roles. Real GitHub examples showcasing best practices. Actionable project ideas you can build right now. Best ways to present your projects and ensure recruiters can find them easily. By the end, you’ll be equipped to craft a compelling portfolio that proves your skills in a tangible way. And when you’re ready for your next career move, remember to upload your CV on DataScience-Jobs.co.uk so that your newly showcased work can be discovered by employers looking for exactly what you have to offer.

Data Science Job Interview Warm‑Up: 30 Real Coding & System‑Design Questions

Data science has become one of the most sought‑after fields in technology, leveraging mathematics, statistics, machine learning, and programming to derive valuable insights from data. Organisations across every sector—finance, healthcare, retail, government—rely on data scientists to build predictive models, understand patterns, and shape strategy with data‑driven decisions. If you’re gearing up for a data science interview, expect a well‑rounded evaluation. Beyond statistics and algorithms, many roles also require data wrangling, visualisation, software engineering, and communication skills. Interviewers want to see if you can slice and dice messy datasets, design experiments, and scale ML models to production. In this guide, we’ll explore 30 real coding & system‑design questions commonly posed in data science interviews. You’ll find challenges ranging from algorithmic coding and statistical puzzle‑solving to the architectural side of building data science platforms in real‑world settings. By practising with these questions, you’ll gain the confidence and clarity needed to stand out among competitive candidates. And if you’re actively seeking data science opportunities in the UK, be sure to visit www.datascience-jobs.co.uk. It’s a comprehensive hub featuring junior, mid‑level, and senior data science vacancies—spanning start‑ups to FTSE 100 companies. Let’s dive into what you need to know.

Negotiating Your Data Science Job Offer: Equity, Bonuses & Perks Explained

Data science has rapidly evolved from a niche specialty to a cornerstone of strategic decision-making in virtually every industry—from finance and healthcare to retail, entertainment, and AI research. As a mid‑senior data scientist, you’re not just running predictive models or generating dashboards; you’re shaping business strategy, product innovation, and customer experiences. This level of influence is why employers are increasingly offering compensation packages that go beyond a baseline salary. Yet, many professionals still tend to focus almost exclusively on base pay when negotiating a new role. This can be a costly oversight. Companies vying for data science talent—especially in the UK, where demand often outstrips supply—routinely offer equity, bonuses, flexible work options, and professional development funds in addition to salary. Recognising these opportunities and effectively negotiating them can have a substantial impact on your total earnings and long-term career satisfaction. This guide explores every facet of negotiating a data science job offer—from understanding equity structures and bonus schemes to weighing crucial perks like remote work and ongoing skill development. By the end, you’ll be well-equipped to secure a holistic package aligned with your market value, your life goals, and the tremendous impact you bring to any organisation.