At a Glance
- Tasks: Design and build advanced data models to uncover revenue opportunities in global education markets.
- Company: Join a leading cloud-based software company driving creative innovation worldwide.
- Benefits: Competitive pay, flexible working, and a commitment to inclusivity.
- Other info: Exciting opportunity for growth in a fast-paced, innovative environment.
- Why this job: Make a real impact by delivering strategic insights that shape the future of education.
- Qualifications: 5+ years in SQL and Python, with experience in data science and predictive analytics.
The predicted salary is between 30000 - 40000 £ per year.
We are seeking a Senior Data Scientist to design, build, and scale an advanced EDU rSAM (Remaining Sales Addressable Market) model to identify and quantify untapped revenue opportunities across global education markets. You will partner closely with cross-functional stakeholders to develop a deep understanding of the education sector, including complex subscription models, institutional procurement structures, and consortium-based purchasing dynamics. This role will sit at the intersection of data science, commercial strategy, and go-to-market execution.
You will collaborate with Data Engineering teams to integrate and operationalise third-party datasets (e.g. student population and institutional metrics), building rich and actionable customer intelligence profiles that inform strategic decision-making. Working alongside Product Marketing and Sales Strategy teams, you will ensure analytical outputs are effectively aligned to go-to-market strategy, pricing frameworks, and broader commercial objectives at the product-offering level.
A key part of the role will involve designing, building, and productionising scalable end-to-end data pipelines, incorporating normalised customer attributes, behavioural signals, and finalised rSAM outputs. You will also combine EDU rSAM outputs with advanced propensity modelling techniques to optimise education-focused sales motions and accelerate customer growth opportunities. Ultimately, you will deliver high-impact strategic insights on market sizing and customer propensity trends to senior leadership, enabling robust, data-driven decision-making and long-term commercial planning.
Skills & Experience
- 5+ years’ advanced SQL experience, with a strong track record in querying, cleansing, integrating, and analysing complex datasets at scale, ideally within Databricks environments.
- Strong Python skills for data manipulation, statistical analysis, and predictive modelling.
- Proven experience developing, validating, and optimising data science models that directly drive revenue growth and commercial performance.
- Experience with propensity modelling and related predictive analytics techniques is highly advantageous.
- Strong ability to translate complex analytical outputs into clear, compelling insights for senior stakeholders and cross-functional audiences.
- Excellent analytical thinking and problem-solving skills, with experience operating in fast-paced, high-growth environments with evolving business priorities.
Aquent is dedicated to improving inclusivity & is proudly an equal opportunities employer. We encourage applications from under-represented groups & are committed to providing support to applicants with disabilities. We aim to provide reasonable accommodation for any part of the employment process, to those with a medical condition, disability or neurodivergence.
Data Science Engineer (210211) in Portsmouth employer: Aquent
As a leading multinational cloud-based software company, we pride ourselves on fostering a dynamic and inclusive work culture that empowers our employees to innovate and excel. Located in the vibrant areas of Reading and London, we offer competitive pay, flexible working arrangements, and ample opportunities for professional growth, ensuring that our team members can thrive both personally and professionally. Join us to be part of a forward-thinking organisation that values diversity and is committed to making a positive impact in the education sector and beyond.
StudySmarter Expert Advice🤫
We think this is how you could land Data Science Engineer (210211) in Portsmouth
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with potential colleagues on LinkedIn. The more you engage, the better your chances of landing that Data Science Engineer role.
✨Tip Number 2
Prepare for interviews by brushing up on your SQL and Python skills. Practice common data science problems and be ready to discuss your past projects. We want to see how you think and solve problems!
✨Tip Number 3
Showcase your work! Create a portfolio of your data science projects, especially those that demonstrate your ability to drive revenue growth. This will give you an edge when discussing your experience with potential employers.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, we love seeing candidates who take the initiative to connect directly with us.
We think you need these skills to ace Data Science Engineer (210211) in Portsmouth
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the Data Science Engineer role. Highlight your SQL and Python skills, and any experience with data science models that have driven revenue growth. We want to see how your background aligns with what we're looking for!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you're passionate about the education sector and how your analytical skills can contribute to our goals. Keep it concise but impactful – we love a good story!
Showcase Relevant Projects:If you've worked on projects that involved building data pipelines or predictive modelling, make sure to mention them. We’re keen to see real-world examples of your work that demonstrate your ability to deliver insights and drive decision-making.
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way to ensure your application gets into the right hands. Plus, it shows us you’re serious about joining our team at StudySmarter!
How to prepare for a job interview at Aquent
✨Know Your Data Inside Out
Make sure you’re well-versed in the datasets relevant to the role. Brush up on your SQL and Python skills, and be ready to discuss how you've used them to drive revenue growth in past projects. Being able to articulate your experience with complex datasets will show that you’re the right fit for the job.
✨Understand the Education Sector
Since this role is focused on the education market, do your homework! Familiarise yourself with subscription models, procurement structures, and purchasing dynamics in education. This knowledge will help you connect with stakeholders and demonstrate your commitment to understanding their needs.
✨Prepare for Technical Questions
Expect to face technical questions about data science models and predictive analytics techniques. Be ready to explain your thought process when developing and optimising these models. Practising common interview questions related to data pipelines and propensity modelling can give you a leg up.
✨Communicate Clearly and Confidently
You’ll need to translate complex analytical outputs into insights for senior stakeholders. Practice explaining your work in simple terms, focusing on how your findings can impact commercial strategy. Clear communication will set you apart and show that you can bridge the gap between data science and business.
