Lead Data Scientist

• 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.

Technologies:

• 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.

• 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.