At a Glance
- Tasks: Lead predictive analytics and develop cutting-edge machine learning models for education.
- Company: Tech-for-Good company transforming education with AI-driven insights.
- Benefits: Competitive salary up to £80k, flexible remote work, and impactful projects.
- Other info: Join a mission-driven team in a high-growth environment.
- Why this job: Shape data strategy and make a real difference in the education sector.
- Qualifications: Experience in Python ML, data analysis, and model evaluation.
The predicted salary is between 80000 - 80000 € per year.
Looking to help shape Data Strategy for a scaling Tech-for-Good business? I'm partnered with an AI‑first data and analytics platform built for schools, multi‑academy trusts and education groups. Their technology connects fragmented school data - attendance, behaviour, wellbeing, assessment, SEND and unstructured documents - and uses a multi‑agent AI system to surface actionable insights for school leaders in seconds.
They are in a high‑growth phase, backed by Innovate UK funding, with a roadmap spanning predictive analytics, supplier intelligence, and international expansion. The team is mission‑driven, remote‑first, and growing quickly - every hire has very meaningful impact.
They are looking for a Senior Data Scientist to lead the predictive analytics capability and their critical programme. You’ll design feature engineering pipelines, select and validate classification and regression models, and establish rigorous evaluation methodology (targeting AUC‑ROC ≥ 0.85) across a 300M+ point education dataset. You’ll be the senior technical lead for ML research, shaping modelling strategy and ensuring outputs are robust, explainable and production‑ready.
Core Responsibilities:- Predictive Model Development: Build and validate supervised learning models (classification & regression) using complex, multi‑source, time‑series‑influenced data.
- Feature Engineering: Design scalable feature pipelines across attendance, behaviour, wellbeing, assessment and SEND datasets.
- Evaluation & Methodology: Establish rigorous evaluation frameworks including AUC‑ROC, precision/recall, cross‑validation and holdback validation.
- ML Platform Ownership: Use Dataiku for pipeline development, model training and deployment.
- Stakeholder Communication: Present findings clearly to non‑technical audiences such as school leaders and grant reviewers.
- Bias & Fairness Analysis: Ensure models meet fairness, transparency and explainability standards.
In return, you’ll get a competitive salary of up to £80k, and very flexible work arrangements across the UK.
Unfortunately we cannot offer sponsorship at this time.
Please contact me at (url removed) to discuss further!
Senior Data Scientist in London employer: Opus Recruitment Solutions
Join a mission-driven team at the forefront of EducationTech, where your work as a Senior Data Scientist will directly impact schools and education groups across the UK. Enjoy the flexibility of remote work while collaborating with a passionate group dedicated to leveraging AI for meaningful change in education. With a competitive salary and opportunities for professional growth in a rapidly scaling environment, this is an excellent place to advance your career while making a difference.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Data Scientist in London
✨Tip Number 1
Network like a pro! Reach out to people in the education tech space, especially those working with data science. Use LinkedIn to connect and engage with them; you never know who might have a lead on that Senior Data Scientist role.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your predictive model development and feature engineering projects. This is your chance to demonstrate your expertise in Python ML and AUC-ROC evaluation methods.
✨Tip Number 3
Prepare for interviews by brushing up on your communication skills. You’ll need to explain complex concepts clearly to non-technical stakeholders, so practice presenting your findings in a straightforward way.
✨Tip Number 4
Don’t forget to apply through our website! We’re all about connecting talent with opportunities, and applying directly can give you an edge. Plus, it shows you’re genuinely interested in joining our mission-driven team.
We think you need these skills to ace Senior Data Scientist in London
Some tips for your application 🫡
Tailor Your CV:Make sure your CV highlights your experience with Python, ML, and any relevant tools like Dataiku and BigQuery. We want to see how your skills align with the role, so don’t be shy about showcasing your achievements in predictive analytics!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you’re passionate about education technology and how you can contribute to our mission. We love seeing genuine enthusiasm, so let your personality come through!
Showcase Your Projects:If you've worked on any relevant projects, especially those involving AUC-ROC or feature engineering, make sure to mention them. We’re keen to see real-world applications of your skills, so include links or descriptions of your work!
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for this exciting opportunity. Plus, it makes the process smoother for everyone involved!
How to prepare for a job interview at Opus Recruitment Solutions
✨Know Your Data Inside Out
Make sure you’re well-versed in the datasets mentioned in the job description. Familiarise yourself with education data types like attendance, behaviour, and wellbeing. Being able to discuss how you would approach feature engineering for these datasets will show your expertise.
✨Showcase Your ML Skills
Prepare to discuss your experience with supervised learning models, especially classification and regression. Be ready to explain your approach to model validation and evaluation metrics like AUC-ROC. This is crucial for demonstrating your technical prowess.
✨Communicate Clearly
Since you'll be presenting findings to non-technical audiences, practice explaining complex concepts in simple terms. Use examples from your past work to illustrate how you’ve communicated insights effectively to stakeholders.
✨Align with Their Mission
Research the company’s mission and values, particularly their focus on Tech-for-Good. Be prepared to discuss how your personal values align with theirs and how you can contribute to their goal of improving education through data.
