Lead Data Scientist
Salary: £100,000 - 100,000 per year
Requirements:- Typically 8 years of relevant industry experience, or a relevant PhD combined with 4-5 years of industry experience.
- Significant experience applying advanced statistical techniques, machine learning, and AI principles to solve complex business problems.
- Strong programming skills in Python, with an emphasis on writing clean, efficient, and maintainable code for scalable and production-grade AI/ML solutions.
- Extensive experience with machine learning frameworks such as Scikit-learn, TensorFlow, and PyTorch.
- Extensive experience designing, deploying, and maintaining production-grade AI/ML solutions, including pipelines, MLOps practices, model versioning, monitoring, and integration with enterprise systems such as Workday.
- Extensive experience designing and implementing generative AI use cases using large language models such as OpenAI GPT and Hugging Face Transformers.
- Proven experience with containerisation and orchestration technologies such as Docker and Kubernetes.
- Proficiency in data engineering, including data wrangling, cleansing, and building production-ready pipelines.
- Extensive experience in cloud environments such as AWS, Azure, or GCP, including cloud-native AI tools like SageMaker, Vertex AI, or Azure ML Studio.
- Demonstrable expertise in creating interactive dashboards and visual analytics using tools such as Streamlit, Plotly, Dash, or D3.js.
- Proven experience leading, mentoring, and formally line-managing data science teams, including performance appraisals and career development support.
- Strong interpersonal and communication skills, with experience managing client engagements and translating business requirements into technical solutions.
- Advanced degree such as an MSc or PhD in Computer Science, Machine Learning, Operational Research, Statistics, or a related field is desirable.
- Proven track record of delivering AI solutions in enterprise SaaS environments, particularly for Workday systems, is desirable.
- Advanced proficiency in relational databases such as PostgreSQL and MySQL, and NoSQL databases such as MongoDB and DynamoDB, is desirable.
- Familiarity with Workday APIs, Workday Prism Analytics, and automated testing frameworks like Kainos Smart is desirable.
- Experience with data engineering and analytics platforms such as Databricks is desirable.
- Active participation in knowledge sharing activities such as conferences, blogs, or internal workshops is desirable.
- Lead the design and delivery of advanced AI/ML solutions that improve the functionality, scalability, and efficiency of our Workday product suite.
- Drive innovations such as predictive analytics for workforce planning, anomaly detection in financial processes, and intelligent automation for Workday applications.
- Collaborate closely with customers and provide thought leadership across the organization.
- Mentor team members and support their development, appraisal, and career progression.
- Carry line management responsibilities for members of the team.
- Contribute actively to the AI solutions behind our fast-growing suite of Workday products, including Kainos Smart, Employee Document Management, and Pay Transparency Analyzer.
- AI
- AWS
- Azure
- Cloud
- D3
- Databricks
- Docker
- GCP
- Support
- Kubernetes
- Machine Learning
- MLOps
- MongoDB
- MySQL
- NoSQL
- PostgreSQL
- PyTorch
- Python
- TensorFlow
- CI/CD
More:
We are Kainos, a people-first company of problem solvers, innovators, and collaborators focused on creating real impact through digital services and cutting-edge Workday solutions. You will join our diverse, ambitious Workday Products division and help shape AI-powered products that support millions of users. We value creativity, collaboration, growth, and inclusion, and we offer a supportive environment where your ideas are valued and your contributions make a difference. We also provide accommodations and adjustments during the recruitment process where needed.
last updated 33 week of 2026