Senior Data Scientist - Workday Products

• We develop high-quality AI and ML solutions for our growing suite of Workday products, including Kainos Smart, Employee Document Management, and Pay Transparency Analyzer.
• We design and deliver advanced AI/ML solutions that improve the functionality, scalability, and efficiency of our Workday product suite.
• We may also carry formal line management responsibilities, including appraisals, for more junior team members.
• We collaborate with engineering teams to deploy AI/ML models into production.
• We work on generative AI use cases to solve real-world problems such as text summarisation, chatbots, and content generation.
• We create interactive visualizations and dashboards to communicate findings effectively.
• We lead client projects and explain technical concepts in clear, non-technical language.
• We mentor junior team members and help foster collaboration within the team.

Technologies:

• AI
• AWS
• Azure
• CI/CD
• Cloud
• Docker
• GCP
• Kubernetes
• LESS
• Machine Learning
• MLOps
• MongoDB
• MySQL
• NoSQL
• PostgreSQL
• PyTorch
• Python
• TensorFlow
• Support

More:

We are Kainos, a people-first company of problem solvers, innovators, and collaborators working to create real impact through digital services and cutting-edge Workday solutions. You will join our diverse and ambitious Workday Products division, where we value creativity, collaboration, and the contribution each person makes. We are committed to diversity, equity, and inclusion, and we aim to give everyone an equal chance to thrive. Our friendly talent acquisition team supports candidates throughout the process and can help arrange accommodations or adjustments if needed.

• We typically look for 4-5 years of relevant industry experience, or less when combined with a relevant PhD.
• We need strong applied knowledge of mathematics, statistics, and machine learning to derive actionable insights from complex datasets.
• We need strong Python programming skills, with the ability to write clean, efficient, and maintainable code for production AI/ML solutions.
• We expect hands-on experience with machine learning frameworks such as Scikit-learn, TensorFlow, or PyTorch.
• We expect experience deploying AI/ML models to production systems in collaboration with engineering teams.
• We look for experience working on generative AI use cases using large language models such as OpenAI GPT or Hugging Face Transformers.
• We require basic experience with cloud technologies such as AWS, Azure, or GCP.
• We expect experience creating interactive visualizations and dashboards with tools such as Dash or Streamlit.
• We need strong interpersonal skills and the ability to lead client projects and explain technical concepts in non-technical terms.
• An advanced degree such as an MSc or PhD in a quantitative field like Computer Science, Machine Learning, Operational Research, or Statistics is desirable.
• We value a proven track record of delivering data science projects, especially in enterprise software or SaaS environments.
• We value familiarity with CI/CD pipelines and MLOps practices, including automated testing, model versioning, and monitoring workflows.
• We value hands-on experience with containerisation and orchestration technologies such as Docker and Kubernetes.
• We value experience cleansing, filtering, and integrating data from relational and NoSQL databases such as PostgreSQL, MySQL, MongoDB, or DynamoDB.
• We value familiarity with Workday data structures, APIs, and reporting tools.
• We value mentoring experience, involvement in performance appraisals, and fostering collaboration within teams.
• We value prior knowledge-sharing activity within teams or through public forums such as conferences or blogs.