Acuity Analytics
Senior Data Scientist (Machine Learning & NLP)

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About Us
Ascent has recently been acquired by Acuity Analytics. This is both a significant milestone for us and a tremendous opportunity for you. Acuity Analytics is a business with a strong global reputation, an impressive client base and ambitious growth plans. We deliver deep insights and domain-led digital transformation to high-growth and heavily regulated organisations. To our customers, we bring a partnership that provides the talent, technology and capability to enhance performance and operational efficiency.
About the Role
We are looking for an experienced Senior Data Scientist to design, build, and optimise intelligent recommendation and ranking solutions that drive better customer outcomes.
Working as part of a collaborative data and engineering team, you will develop production-ready machine learning models, leverage behavioural analytics, and apply modern NLP techniques to solve complex business challenges. You'll work with large-scale datasets using Databricks and Spark, taking models from experimentation through to deployment while continuously improving live system performance.
This is an exciting opportunity for someone who enjoys solving real-world problems and building scalable machine learning solutions that deliver measurable business impact.
Skills and Experience Required
Core Skills
- Strong commercial experience in Machine Learning and predictive modelling.
- Experience with behavioural analytics and user behaviour modelling.
- Hands-on experience with Natural Language Processing (NLP).
- Strong experience using Databricks and Apache Spark.
- Experience building recommendation or ranking systems.
- Strong knowledge of statistical modelling and model evaluation techniques.
- Experience designing and analysing product experimentation (A/B testing and experimentation frameworks).
- Strong programming skills in Python and experience working with machine learning libraries.
- Experience working with large datasets and developing scalable ML solutions.
Reasons to use Rodeo
I’m in my final year doing Economics and I don’t know whether to apply for grad schemes now or do a masters first. What do you think?
Honest answer — it depends on where you want to end up. A lot of top grad schemes (Big 4, civil service, banking) don’t need a masters. Let’s look at the ones you’d be competitive for now, and we can decide if a masters actually adds anything.
Also worth knowing: most autumn 2026 applications are open now. Timing matters more than you think.
Start with a chat, not a search bar
Grad scheme, placement, apprenticeship? Not sure what you want yet — that's fine. Your agent talks it through with you and turns "I have no idea" into a shortlist.
Graduate Consultant — 2026 Scheme
Why you're a good match
StrongYour economics background and your summer at a regional bank line up with what PwC looks for on the consulting scheme. Applications close in four weeks.
See breakdownIt searches the market for you
Every day your agent scans the market matching roles against what actually matters to you, not just keywords on a CV.
Why you're a good match
You’ve got the grades and the economics background, and your bank internship is exactly the experience this scheme looks for. Apply soon — deadlines close within the month.
Experience fit
Your summer at the bank plus your econometrics coursework map directly to the day-one responsibilities on this scheme — client modelling, market briefings, and deal support.
Only hits
No noise. No "maybe this fits." Just roles with a clear explanation of why they're right — and where to focus when applying.
Soft Skills
- Strong analytical and problem-solving skills.
- Ability to communicate technical concepts to both technical and non-technical stakeholders.
- Collaborative approach with experience working in cross-functional Agile teams.
- Passion for building production-quality machine learning solutions.
- Ability to balance experimentation with delivering measurable business value.
What You Will Do
- Design, build, and deploy machine learning models for recommendation and ranking systems.
- Analyse behavioural data to identify patterns and opportunities for optimisation.
- Develop NLP solutions to enhance intelligent matching and search capabilities.
- Build scalable machine learning pipelines using Databricks and Spark.
- Design, execute, and evaluate product experiments to improve model performance.
- Monitor, optimise, and continuously improve production machine learning models.
- Collaborate with Data Scientists, Data Engineers, Product Managers, and stakeholders to deliver high-impact solutions.
- Apply statistical techniques to evaluate model effectiveness and support data-driven decision making.


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Nice to Have
- Experience building production-grade recommendation or matching systems within industries such as e-commerce, marketplaces, recruitment, property, or financial services.
- Experience improving live matching performance rather than developing research prototypes.
- Experience deploying and monitoring machine learning models in cloud environments.
- Familiarity with MLOps principles and model lifecycle management.
Why Join Us
People are at the heart of our business. By investing in people, we achieve exceptional results for our clients and create new opportunities for our teams to thrive. Join us and work on innovative machine learning solutions that solve real business challenges while collaborating with talented teams across data, engineering, and analytics. Check out this page for more details.
If you have any questions contact our Talent Acquisition team on ta.admin@acuityanalytics. For more details about Acuity Analytics please see here: Read here.
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