At a Glance
- Tasks: Lead the design and delivery of advanced AI/ML solutions for innovative Workday products.
- Company: Join Kainos, a people-first tech company focused on collaboration and creativity.
- Benefits: Competitive salary, supportive culture, and opportunities for personal and professional growth.
- Other info: Embrace diversity and inclusion in a dynamic work environment.
- Why this job: Make a real impact with cutting-edge technology in a diverse and ambitious team.
- Qualifications: 8+ years in data science or relevant PhD, strong programming skills in Python.
The predicted salary is between 63000 - 77000 £ per year.
hackajob is collaborating with
Kainos to connect them with exceptional professionals for this role.
Join Kainos and Shape the Future
At Kainos, we're problem solvers, innovators, and collaborators - driven by a shared mission to create real impact.
Whether we're transforming digital services for millions, delivering cutting-edge Workday solutions, or pushing the boundaries of technology, we do it together.
We believe in a people-first culture , where your ideas are valued, your growth is supported, and your contributions truly make a difference.
Here, you'll be part of a diverse, ambitious team that celebrates creativity and collaboration.
Ready to make your mark?
Join us and be part of something bigger.
As a Lead Data Scientist within Kainos Workday Products division you will play a pivotal role in actively contributing to the AI solutions behind our fast growing suite of Workday products - including Kainos Smart (Smart Test, Smart Audit and Smart Shield), Employee Document Management and Pay Transparency Analyzer.
You will lead the design and delivery of advanced AI/ML solutions that improve the functionality, scalability, and efficiency of our Workday product suite.
You will focus on cutting edge innovations, such as predictive analytics for workforce planning, anomaly detection in financial processes, and intelligent automation for Workday applications.
You will collaborate closely with customers, mentor your team, and provide thought leadership across the organization.
Alongside this strategic and technical ownership, you will carry line management responsibilities, including the development, appraisal, and career progression of members of your team.
Essential Experience
- Typically 8+ years of relevant industry experience, or a relevant Ph D 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 to enable scalable and production-grade AI/ML solutions.
- Extensive experience with machine learning frameworks (e. g., Scikit-learn, Tensor Flow, Py Torch), with the ability to design, implement, and optimise scalable solutions while guiding teams in the effective use of these tools.
- Extensive expertise in designing, deploying, and maintaining production-grade AI/ML solutions, including pipelines, MLOps practices (e. g., CI/CD pipelines, model versioning, monitoring), and seamless integration with enterprise systems such as Workday.
- Extensive experience designing and implementing generative AI use cases, leveraging large language models (e. g., Open AI GPT, Hugging Face Transformers) to deliver scalable solutions for tasks such as conversational AI, document summarisation, or content creation.
- Proven experience with containerisation and orchestration technologies (e. g., Docker, Kubernetes), including their use in designing scalable, cloud-native AI/ML systems.
- Proficiency in data engineering, including data wrangling, cleansing, and creating pipelines that integrate seamlessly into production environments.
- Extensive experience in cloud environments (AWS, Azure, or GCP), including leveraging cloud-native AI tools like Sage Maker, 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 conducting performance appraisals and supporting career development and progression.
- Strong interpersonal and communication skills, with a track record of managing client engagements and translating business requirements into actionable technical solutions.
Desirable Experience
- Advanced degree (MSc or Ph D) in Computer Science, Machine Learning, Operational Research, Statistics, or a related field.
- Proven track record of delivering AI solutions in enterprise Saa S environments, particularly for Workday systems.
- Advanced proficiency in relational databases (e. g., Postgre SQL, My SQL), No SQL databases (e. g., Mongo DB, Dynamo DB).
- Familiarity with Workday APIs, Workday Prism Analytics, and automated testing frameworks like Kainos Smart.
- Knowledge of data engineering and analytics platforms such as Databricks, with experience in leveraging them for scalable data processing and machine learning workflows.
- Active participation in knowledge sharing activities, such as conferences, blogs, or internal workshops, to promote thought leadership.
- Embracing our differences
At Kainos, we believe in the power of diversity, equity and inclusion.
We are committed to building a team that is as diverse as the world we live in, where everyone is valued, respected, and given an equal chance to thrive.
We actively seek out talented people from all backgrounds, regardless of age, race, ethnicity, gender, sexual orientation, religion, disability, or any other characteristic that makes them who they are.
We also believe every candidate deserves a level playing field.
Our friendly talent acquisition team is here to support you every step of the way, so if you require any accommodations or adjustments, we encourage you to reach out.
We understand that everyone's journey is different, and by having a private conversation we can ensure that our recruitment process is tailored to your needs.
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Lead Data Scientist - Workday Products employer: hackajob
At hackajob, we pride ourselves on being an exceptional employer that fosters a culture of innovation and inclusivity. Our diverse team thrives in a high-performance environment where your contributions directly impact our multi-asset platform's success. With ample opportunities for professional growth and a commitment to employee development, joining us means being part of a forward-thinking company that values your expertise and ambition.
StudySmarter Expert Advice🤫
We think this is how you could land Lead Data Scientist - Workday Products
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We think you need these skills to ace Lead Data Scientist - Workday Products
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
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Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at hackajob. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at hackajob
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
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✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at hackajob!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.