Senior Data Scientist

Benifex
Southampton
3 weeks ago
Create job alert
Who are Benifex?

We are a fast-moving technology company, and one of the most successful providers of online reward and benefits solutions in the world. We believe that everyone deserves an exceptional experience at work, every day, and build workplace technology that makes this happen. Benifex’s mission is to build remarkable experiences that employees love. Today Benifex supports more than five million employees in over 3,000 organisations across more than 100 countries. To help us on our quest to be the best, we need brilliant people on board and that’s where you come in. 🚀


Why should you apply? 🌟

  • Challenge: Implement a scalable data platform to meet our internal and external analytics needs
  • Impact: Be one of the first hires to help build a world class data engineering function.
  • Scale: A key pillar of our global growth plan is data, allowing us to make better decisions and deliver more value to our users
  • Sunday Times Best Place to Work 2025 and Best Large Tech Company to Work for 2025
  • Work for a profitable, fast-growing market leader in the online reward and benefits space

Please note we are unable to offer visa sponsorship and require to people to be based in the UK or Ireland for this position


Great benefits:

  • 💰 £70,000-90,000
  • 💻 Tech setup of your choice (MacBook Pro or equivalent, monitors, etc.)
  • 📚 £/€800 annual learning budget, plus two hours per week as ‘Focus Fridays’.
  • 🤸 Flexible work – choose a working setup that works for you, our only ask is to see you once a month in the office and you must be based in the UK or Ireland.
  • 💸 Full access to our comprehensive benefits package, including discounts from hundreds of high street brands, salary sacrifice schemes across Finance, Health, Tech, and more
  • ✈️ 25 days holiday plus your local bank holidays
  • 🎂 Your birthday off
  • ❤️ Two half day wellbeing days
  • 🩺 Healthcare cash plan to cover the costs of day-to-day healthcare
  • 🧠 Employee Assistance Plan 24/7 365 support
  • 🤒 Income Protection (75%) and life assurance (4x salary)
  • 💰 Referral bonuses
  • 🌟 Enhanced parental leave package - 26 weeks fully paid maternity leave and 4 weeks fully paid paternity leave
  • ✈️ Work from Anywhere policy for 90 days
  • 🏖️ Buy and Sell scheme for holidays
  • 💳 £50 monthly allowance to spend on whatever takes your fancy, your very own Benifex card will be topped up at the start of each month!

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 are we looking for? 🔎

  • Strong hands-on experience in Python for data analysis and shallow and deep machine modelling, using libraries such as NumPy, Pandas, scikit-learn, TensorFlow or PyTorch.
  • Experience building forecasting and predictive models with clear understanding of time-series techniques and model validation.
  • Strong grounding in statistical analysis and exploratory data techniques.
  • Experience designing or contributing to model evaluation frameworks, including accuracy, stability, and drift metrics.
  • Solid understanding of data preparation, data quality, and feature engineering.
  • Ability to communicate modelling approaches and insights to technical and non-technical stakeholders.
  • Comfortable working in a collaborative, cross-functional environment where models inform product decisions.

Bonus Points:

  • 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.


Our 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.


#J-18808-Ljbffr

Related Jobs

View all jobs

Senior Data Scientist

Senior Data Scientist (GenAI)

Senior Data Scientist

Senior Data Scientist & Machine Learning Researcher

Senior Data Scientist (GenAI)

Senior Data Scientist (GenAI)

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

How Many Machine Learning Tools Do You Need to Know to Get a Machine Learning Job?

Machine learning is one of the most exciting and rapidly growing areas of tech. But for job seekers it can also feel like a maze of tools, frameworks and platforms. One job advert wants TensorFlow and Keras. Another mentions PyTorch, scikit-learn and Spark. A third lists Mlflow, Docker, Kubernetes and more. With so many names out there, it’s easy to fall into the trap of thinking you must learn everything just to be competitive. Here’s the honest truth most machine learning hiring managers won’t say out loud: 👉 They don’t hire you because you know every tool. They hire you because you can solve real problems with the tools you know. Tools are important — no doubt — but context, judgement and outcomes matter far more. So how many machine learning tools do you actually need to know to get a job? For most job seekers, the real number is far smaller than you think — and more logically grouped. This guide breaks down exactly what employers expect, which tools are core, which are role-specific, and how to structure your learning for real career results.

What Hiring Managers Look for First in Machine Learning Job Applications (UK Guide)

Whether you’re applying for machine learning engineer, applied scientist, research scientist, ML Ops or data scientist roles, hiring managers scan applications quickly — often making decisions before they’ve read beyond the top third of your CV. In the competitive UK market, it’s not enough to list skills. You must send clear signals of relevance, delivery, impact, reasoning and readiness for production — and do it within the first few lines of your CV or portfolio. This guide walks you through exactly what hiring managers look for first in machine learning applications, how they evaluate CVs and portfolios, and what you can do to improve your chances of getting shortlisted at every stage — from your CV and LinkedIn profile to your cover letter and project portfolio.

MLOps Jobs in the UK: The Complete Career Guide for Machine Learning Professionals

Machine learning has moved from experimentation to production at scale. As a result, MLOps jobs have become some of the most in-demand and best-paid roles in the UK tech market. For job seekers with experience in machine learning, data science, software engineering or cloud infrastructure, MLOps represents a powerful career pivot or progression. This guide is designed to help you understand what MLOps roles involve, which skills employers are hiring for, how to transition into MLOps, salary expectations in the UK, and how to land your next role using specialist platforms like MachineLearningJobs.co.uk.