Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

AI Scientist

Zellis
Watford
6 months ago
Applications closed

Related Jobs

View all jobs

Data Science Manager (Applied AI)

Director of AI Optimization and Productization - R&D Data Science & Digital Health

Data Science and AI Industrial Placement (Manchester)

Senior Data Engineer

Senior Data Engineer

Senior Data Engineer

About the roleAs an AI Scientist at Zellis you'll play a pivotal role in embedding AI-driven solutions across the Zellis HR, Workforce Management and Payroll platform and driving through their adoption. You'll work within a small, highly creative and research-driven team, designing, developing and deploying compute-efficient, powerful, and safe AI models that provide tangible value to our clients. Our mission is to redefine how AI can expand Zellis’ client base, ensuring AI goes beyond surface-level functionality to drive meaningful transformation across HR and pay solutions.You'll develop and implement AI technologies that enhance automation, decision-making, and predictive capabilities. You'll also ensure our AI solutions adhere to strict ethical, privacy, and security standards while maximising business impact.At Zellis, we balance research with practical deployment, ensuring that AI innovations translate into business value. We embrace a fast-paced, entrepreneurial mindset, enabling us to iterate rapidly and refine our AI strategies based on continuous learning and real-world feedback.In this role your key responsibilities will include:AI Research and Model Development: * Conducting research in AI, using a full range of machine learning and GenAI techniques to develop solutions across the entire HR lifecycle. * Designing and optimising AI that enhances automation and decision-making. * Ensuring AI models are scalable and efficient for real-world enterprise deployment. * Experimenting with different machine learning and GenAI techniques, including prompt engineering, RAG (Retrieval Augmented Generation), fine-tuning of LLMs, RLHF (reinforcement learning with human feedback), and adversarial techniques. * Evaluating AI model performance using statistical and business-driven metrics. * Working on natural language to SQL AI transformations to extract data value. * Working on natural language to other meta-language translation / transformation (e.g. LaTeX/mermail.io for diagramming, or natural language to code). * Speech to text. * Developing explainable AI approaches for transparency and trust.AI Integration into HR, Workforce Management, and Payroll Systems: * Collaborating with the Technology teams / Engineers to integrate AI solutions across all HR and payroll modules. * Automating repetitive HR tasks like payroll processing and compliance checks. * Implementing AI-driven workforce forecasting and scheduling. * Developing AI-powered insights for HR leaders to improve talent management. * Enhancing employee self-service with AI bots, assistants, and workspaces.AI Ethics, Privacy, and Security: * Designing AI systems that are safe, unbiased, and compliant with GDPR. * Working with Legal teams to assess and mitigate AI-related risks. * Ensuring AI models do not reinforce biases in HR processes. * Implementing privacy-preserving techniques in AI solutions.Collaboration and Cross-Functional Work: * Working with Product Managers, Engineers, and business stakeholders to define AI goals. * Communicating AI concepts in a business-friendly manner. * Leading AI experimentation initiatives and contributing to internal strategy discussions. * Engaging with customers to understand AI needs and create practical solutions. * Continuous learning and innovation. * Staying up-to-date with AI and ML research relevant to HR and workforce management. * Exploring new techniques in deep learning and generative AI. * Publishing research findings in internal reports and industry conferences. * Prototype and testing AI models before full-scale deployment.Skills & experience requiredTechnical Expertise:- Understanding of transformer architectures, and large-scale language models.- Experience with data engineering, model optimisation, and distributed computing.- Strong programming skills in JavaScript, or Python / other AI-related languages.- Strong SQL and data analytics skills.- Familiarity with cloud platforms (AWS and Azure) for AI deployment.- Knowledge of MLOps principles for scaling AI models.- Understanding of knowledge graphs, semantic search, and vector databases.AI Ethics and Responsible AI:- Awareness of AI ethics, bias mitigation, and fairness in models.- Understanding of GDPR and compliance frameworks for AI in HR applications.- Ability to design fair and interpretable AI systems.Problem Solving and Critical Thinking:- Strong analytical skills to improve AI model performance.- Ability to develop innovative AI-driven solutions for business challenges.Business Acumen and HR Domain Knowledge:- Understanding of HR, payroll, and workforce management processes would be advantageous.- Ability to translate AI research into commercially viable products.- Experience working with HR datasets and organisational analytics.Collaboration and Communication:- Ability to explain AI concepts to non-technical stakeholders.- Experience working in cross-functional teams.- Strong documentation skills for AI research and best practices.- Enthusiasm for mentoring and knowledge sharing.Adaptability and Continuous Learning:- Ability to work in a fast-paced, entrepreneurial setting.- Willingness to experiment with emerging AI technologies.- Commitment to ongoing learning in AI and HR tech.- Strategic and product-focused thinking.- Vision for AI-driven business expansion at Zellis.- Focus on delivering measurable AI value to HR professionals.- Ability to balance long-term AI research with short-term business impact.- Significant experience working as a Software Engineer, with a focus on growth engineering or related field, and strong full-stack practical coding skills.Benefits & cultureAt Zellis we create AI-enabled HR, workforce management and payroll products and services, to power exceptional employee experiences so that you and your people do better. Our multi-award-winning products pay over five million employees a year, with almost half (42%) of the FTSE 100, 50% of the top retailers and 30% of the top universities in the UK & Ireland as customers, making us the largest provider of Payroll and HR software and managed services.Our vision is to be the clear leader in pay, reward, analytics, and people experiences. We're passionate about creating an environment where people want to join, belong to, and be part of a progressive organisation. Our values, which were defined with input from of our 3,000+ colleagues, we live and breathe every day:- Unstoppable together.- Always learning.- Make it count.- Think scale.Our people are critical to our ongoing success; we’re proud of our inclusive culture that gives you the platform to grow, challenge the status quo and play a crucial role in further enhancing our market position as the leading provider of HR & Payroll software and services. With Zellis you’ll have the chance to stretch and challenge yourself in an environment that’s varied, flexible and hugely supportive.We also love to reward and recognise our brilliant colleagues. As part of your benefits package, you’ll receive:- A competitive base salary.- 25 days annual leave, plus your birthday off and the opportunity to buy additional holiday.- Private medical insurance.- Life assurance 4x salary.- Enhanced pension scheme with company contributions up to 8.5%.- A huge range of additional flexible benefits across financial & personal wellbeing, lifestyle & leisure

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.

Data Science Recruitment Trends 2025 (UK): What Job Seekers Need To Know About Today’s Hiring Process

Summary: UK data science hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise rigorous problem framing, high‑quality analytics & modelling, experiment/causality, production awareness (MLOps), governance/ethics, and measurable product or commercial impact. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for product/data scientists, applied ML scientists, decision scientists, econometricians, growth/marketing analysts, and ML‑adjacent data scientists supporting LLM/AI products. Who this is for: Product/decision/data scientists, applied ML scientists, econometrics & causal inference specialists, experimentation leads, analytics engineers crossing into DS, ML generalists with strong statistics, and data scientists collaborating with platform/MLOps teams in the UK.

Why Data Science Careers in the UK Are Becoming More Multidisciplinary

Data science once meant advanced statistics, machine learning models and coding in Python or R. In the UK today, it has become one of the most in-demand professions across sectors — from healthcare to finance, retail to government. But as the field matures, employers now expect more than technical modelling skills. Modern data science is multidisciplinary. It requires not just coding and algorithms, but also legal knowledge, ethical reasoning, psychological insight, linguistic clarity and human-centred design. Data scientists are expected to interpret, communicate and apply data responsibly, with awareness of law, human behaviour and accessibility. In this article, we’ll explore why data science careers in the UK are becoming more multidisciplinary, how these five disciplines intersect with data science, and what job-seekers & employers need to know to succeed in this transformed field.

Data Science Team Structures Explained: Who Does What in a Modern Data Science Department

Data science is one of the most in-demand, dynamic, and multidisciplinary areas in the UK tech and business landscape. Organisations from finance, retail, health, government, and beyond are using data to drive decisions, automate processes, personalise services, predict trends, detect fraud, and more. To do that well, companies don’t just need good data scientists; they need teams with clearly defined roles, responsibilities, workflows, collaboration, and governance. If you're aiming for a role in data science or recruiting for one, understanding the structure of a data science department—and who does what—can make all the difference. This article breaks down the key roles, how they interact across the lifecycle of a data science project, what skills and qualifications are typical in the UK, expected salary ranges, challenges, trends, and how to build or grow an effective team.