Role overview
We are seeking a skilled Data Scientist to join our AI Squad and play a key role in building the analytical and predictive capabilities that power Benifex products. You will work closely with engineers, product managers, and data stakeholders to develop models that turn our HR and benefits data into meaningful insights for our customers.
This is a hands-on role focused on forecasting, statistical modelling, exploratory analysis, and applied machine learning. You will contribute to the intelligence behind Brain, our HR AI assistant, helping ensure that the insights we deliver are accurate, reliable, and actionable.
You will join a collaborative team across Cebu and the UK, working in a dynamic environment where we solve complex problems together and continuously learn.
*Responsibilities
The focus for the next 12 months will be:**
- Design and build forecasting and predictive models for benefits spend, cost drivers, headcount trends, and benefit utilisation.
- Conduct exploratory data analysis to uncover patterns, anomalies, and drivers within our HR and benefits datasets.
- Develop well-structured feature sets and work with Data Engineering to improve data readiness and data quality.
- Create evaluation and benchmarking frameworks to assess model performance, identify drift, and improve reliability over time.
- Communicate insights, modelling decisions, and trade-offs clearly to AI, Product, and Data teams.
- Support the refinement of AI components by improving model inputs, analysing outcomes, and feeding insights into AI system improvements.
- Stay up to date with developments in statistics, forecasting techniques, and applied machine learning.
LLM-focused activities (secondary):
- Support evaluation of LLM outputs through structured benchmarking.
- Contribute to improvements in retrieval and context pipelines by analysing data and output behaviour.
- Help optimise prompts and model inputs where modelling intersects with LLM tasks.
What we're looking for
- Experience working with HR, finance, or operational datasets.
- Familiarity with embeddings or retrieval methods, especially where they support downstream modelling.
- Exposure to LLM evaluation or prompt optimisation.
- Awareness of basic ML engineering principles for deploying or packaging models, even if you are not responsible for full MLOps.
- Experience with cloud environments or BI tools.
- Exposure backend engineering, including REST APIs (Java, Springboot) and full-stack architecture.
Even if you don't meet all of the requirements for this role, we encourage you to apply! We are looking for talented and passionate individuals who are eager to learn and grow. We also offer a variety of other roles, so please check out our careers page to see if there is something else that might be a good fit for you.
Interview process
Benifex understands the need to have a fast and efficient process, the below will all be completed in the shortest time possible.
Initial informal call with the Talent team
Interview with our Engineering Manager 30 min
Technical Task
Technical Interview - 60 min
Final interview with VP of Engineering - 30-45 min
*We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, colour, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.
We are committed to creating a diverse and inclusive workplace where everyone feels welcome and respected. We believe that diversity and inclusion are essential to our success, and we are proud to be an equal opportunity employer.
We are a proud member of the Disability Confident employer scheme.
If you require any reasonable adjustments at any stage during the recruitment process, please let us know with your application.