Data Scientist

Old Street
3 weeks ago
Applications closed

Related Jobs

View all jobs

Data Scientist

Data Scientist

Data Scientist

Data Scientist - London

Data Scientist | London | AI-Powered SaaS Company

Data Scientist - Remote

Data Scientist
Salary Circa £45,000 - £60,000
Location London (Hybrid)
Permanent
Full time / Part time
Closing Date: April 28th 2025
We currently have an opportunity for a Data Scientist to join our team. This role is open to flexible working, with 21 hours per week a minimum.
The ASA is the UK’s regulator of advertising across all media, including online. Our work includes taking proactive action against misleading, harmful, offensive or otherwise irresponsible ads and acting on complaints. Our Data Science team uses data and machine learning to proactively monitor online advertising and is responsible for our Active Ad Monitoring system, which captures and processes more than 3 million ads each month, allowing us to respond rapidly and effectively to important issues. We are seeking someone with prior professional experience working with complex datasets to join this team.
Reporting to the Head of Data Science, in this role you will work with the ads captured by the ASA’s Active Ad Monitoring system. You will work with images, videos and especially the text of ads from social media, search and web display. You will collaborate with experts across a range of advertising sectors to understand their needs. You will work primarily in Python to perform analysis to extract insight about prevalence of potential issues and help inform priorities. You will also train machine learning models and use LLM-based tools to filter large volumes of ads to find those that are relevant, or that break the rules. You will take end-to-end ownership of projects and will directly see how your work protects people in the UK from harmful and misleading content.
Current projects within the team focus on diverse topics such as ensuring influencer marketing on social media follows advertising rules; monitoring the green claims companies make to consumers; and making sure ads for weight loss medications are responsible. You will report directly to the Head of Data Science, working alongside other Data Scientists and Data Engineers. As part of a developing team, you will have the chance to help shape our approach and ultimately the way data-led insight and machine learning is used to regulate advertising.
Candidates must be able to work with data in Python, and have an understanding of statistical concepts and machine learning. You must be comfortable communicating complex ideas to non-technical people, and you must believe in our mission as a regulator. Candidates should either have prior data science experience, or have done similar work in another setting e.g. academic research in a data-intensive field or as an analyst working with Python. Please note we do not have a sponsorship licence and are unable to sponsor visas.
We think the ASA is a great place to work. We have a culture that’s open, friendly and collaborative, with a real focus on making the right decisions in the right way, and learning while we’re doing it. We’re always looking to improve diversity within our teams, and we’d love to hear from people from diverse backgrounds for this role. We encourage applications from candidates who are likely to be underrepresented in this field of work. We operate a hybrid working model and office attendance is required 40% of your contracted hours.
How to apply: If you’re interested in applying for this role, please review the job description below and complete the online questions telling us how you meet the requirements of the role and how you can contribute to our success.
Please note that we'll keep the ad open till we fill the post and will be reviewing applications as they come in.
Role: The Data Scientist will deliver analysis and machine learning projects that address real-world challenges faced by the ASA in the regulation of online advertising.
Responsibilities
With support from the Head of Data Science and time to learn new skills where needed the Data Scientist will:


  • Take end-to-end ownership of data science projects

  • Communicate with stakeholders to understand the challenges they face daily when regulating advertising, translating these into technical solutions

  • Work with a range of unstructured data such as text, images and videos from a variety of sources

  • Apply statistical and machine learning techniques to these datasets including LLM-based tools

  • Deliver insights that inform the focus and approach taken when teams deliver regulation in specific areas

  • Deploy models into production to support ongoing monitoring of compliance and proactive identification of potentially problematic content

We are looking for candidates who have:


  • Prior relevant experience – Experience working with complex datasets either as a Data Scientist, or another relevant role e.g. in academic research or an analyst role.

  • Programming Skills – Experience writing code to manipulate data and apply statistical or machine learning techniques in Python

  • Statistics/Machine Learning – Experience applying at least a couple of statistical and/or machine learning techniques and an understanding of how those techniques work behind the scenes

  • Communication – The ability to communicate technical solutions to non-technical stakeholders, explaining the value of your work

The ideal candidate also has the following personal attributes:


  • Interest in our mission - A desire to make a positive contribution to the regulation of advertising in the UK

  • Creative problem solver - Able to think about a complex problem from multiple perspectives, identifying potential solutions

  • Takes ownership - Willing to take responsibility for delivering a project end-to-end

  • Critical thinking - Able to reflect on their work, spotting mistakes and weaknesses and correcting them where practical

  • Team worker - Wants to collaborate with a team of individuals with mixed expertise and backgrounds, making a positive contribution to team culture

Please note we do not have a sponsorship licence and are unable to sponsor visas

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.

Negotiating Your Machine Learning Job Offer: Equity, Bonuses & Perks Explained

How to Secure a Compensation Package That Matches Your Technical Mastery and Strategic Influence in the UK’s ML Landscape Machine learning (ML) has rapidly shifted from an emerging discipline to a mission-critical function in modern enterprises. From optimising e-commerce recommendations to powering autonomous vehicles and driving innovation in healthcare, ML experts hold the keys to transformative outcomes. As a mid‑senior professional in this field, you’re not only crafting sophisticated algorithms; you’re often guiding strategic decisions about data pipelines, model deployment, and product direction. With such a powerful impact on business results, companies across the UK are going beyond standard salary structures to attract top ML talent. Negotiating a compensation package that truly reflects your value means looking beyond the numbers on your monthly payslip. In addition to a competitive base salary, you could be securing equity, performance-based bonuses, and perks that support your ongoing research, development, and growth. However, many mid‑senior ML professionals leave these additional benefits on the table—either because they’re unsure how to negotiate them or they simply underestimate their long-term worth. This guide explores every critical aspect of negotiating a machine learning job offer. Whether you’re joining an AI-focused start-up or a major tech player expanding its ML capabilities, understanding equity structures, bonus schemes, and strategic perks will help you lock in a package that matches your technical expertise and strategic influence. Let’s dive in.

Machine Learning Jobs in the Public Sector: Opportunities Across GDS, NHS, MOD, and More

Machine learning (ML) has rapidly moved from academic research labs to the heart of industrial and governmental operations. Its ability to uncover patterns, predict outcomes, and automate complex tasks has revolutionised industries ranging from finance to retail. Now, the public sector—encompassing government departments, healthcare systems, and defence agencies—has become an increasingly fertile ground for machine learning jobs. Why? Because government bodies oversee vast datasets, manage critical services for millions of citizens, and must operate efficiently under tight resource constraints. From using ML algorithms to improve patient outcomes in the NHS, to enhancing cybersecurity within the Ministry of Defence (MOD), there’s a growing demand for skilled ML professionals in UK public sector roles. If you’re passionate about harnessing data-driven insights to solve large-scale problems and contribute to societal well-being, machine learning jobs in the public sector offer an unparalleled blend of challenge and impact. In this article, we’ll explore the key reasons behind the public sector’s investment in ML, highlight the leading organisations, outline common job roles, and provide practical guidance on securing a machine learning position that helps shape the future of government services.

Contract vs Permanent Machine Learning Jobs: Which Pays Better in 2025?

Machine learning (ML) has swiftly become one of the most transformative forces in the UK technology landscape. From conversational AI and autonomous vehicles to fraud detection and personalised recommendations, ML algorithms are reshaping how organisations operate and how consumers experience products and services. In response, job opportunities in machine learning—including roles in data science, MLOps, natural language processing (NLP), computer vision, and more—have risen dramatically. Yet, as the demand for ML expertise booms, professionals face a pivotal choice about how they want to work. Some choose day‑rate contracting, leveraging short-term projects for potentially higher immediate pay. Others embrace fixed-term contract (FTC) roles for mid-range stability, or permanent positions for comprehensive benefits and a well-defined career path. In this article, we will explore these different employment models, highlighting the pros and cons of each, offering sample take‑home pay scenarios, and providing insights into which path might pay better in 2025. Whether you’re a new graduate with a machine learning degree or an experienced practitioner pivoting into an ML-heavy role, understanding these options is key to making informed career decisions.