Associate Data Scientist
Legal Counsel - 12 month FTC at Rightmove Greenhouse LondonEst. Est. GBP 40,000–55,000 / yearJunior
Estimated range based on role, country and industry — not published by the company.
Key requirements
- Python
- Sql
- Dbt
- Aws
- Azure
- Gcp
- Machine Learning
- Deep Learning
- Data Science
Our vision is to give everyone the belief they can make their move. We aim to make moving simpler, by giving everyone the best place to turn to and return to for access to the tools, expertise, trust, and belief to make it happen.
We’re home to the UK’s largest choice of properties and are the go-to destination for millions of people planning their next move, reading the latest industry news, or just browsing what’s on the market.
We’re looking for an Associate Data Scientist to join Rightmove’s growing Data, Analytics & AI team. This is an excellent opportunity for someone at an early stage in their career to apply machine learning and AI to real problems in the UK property market, while building strong foundations in data science.
You’ll work closely with experienced data scientists, machine learning engineers and data engineers, contributing to well-defined pieces of larger projects while receiving close support and guidance as you build your skills. This role would suit someone who is keen to learn, enjoys solving practical problems, and wants to develop their skills within a collaborative, product-focused environment.
What you’ll be doing
A typical week may involve:
Building, training and evaluating machine learning models using standard libraries and techniques, under the guidance of more experienced colleagues
Tuning model hyperparameters, interpreting results and clearly explaining what a model does and how well it performs
Writing SQL and Python to query, clean and transform datasets, and carrying out data quality checks
Applying descriptive statistics and creating clear visualisations to summarise data and highlight meaningful patterns
Supporting the design and evaluation of experiments and the monitoring of key product metrics
Working with machine learning engineers and data engineers to prepare data and support the move of models from experimentation into production
Helping monitor deployed models, flagging issues such as performance degradation or data drift
Exploring new techniques, including LLMs and generative AI, through small prototypes and proofs of concept
Writing clear, maintainable code and following team practices such as version control, code review and reproducibility
Using AI tools responsibly and reliably to work more efficiently, while reviewing, testing and taking ownership of anything, they help you produce
Following our AI model standards, so that the models we build are robust, well documented and responsibly deployed
Keeping your team informed about progress and challenges, and sharing what you learn across the data and AI community
Collaborating with product, engineering, and data teams to support delivery of AI features
We’re looking for someone who
Has a solid understanding of core machine learning concepts, including standard algorithms, loss functions and evaluation metrics
Has some experience with Python and SQL (through academic work, projects, or early commercial experience)
Is familiar with at least one ML library or framework (e.g. scikit-learn, XGBoost, PyTorch or TensorFlow)
Has a working knowledge of descriptive statistics and data visualisation, and can interpret results sensibly
Is comfortable using Git and basic development workflows
Has strong problem-solving skills, attention to detail and a curious, creative mind
Is proactive, open to feedback and keen to keep up with developments in data science, ML and generative AI
Communicates clearly to technical and non-technical colleagues and enjoys working as part of a team
Nice to have
A degree in Statistics, Computer Science, Data Science, Mathematics, or a related quantitative or STEM subject
Internship, placement year, or project experience involving machine learning or data analysis
Exposure to cloud platforms and tools (e.g. GCP, BigQuery, Verte
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