At a Glance
- Tasks: Lead the design of advanced predictive models and mentor a team of data scientists.
- Company: Join a mission-driven fintech-adjacent proptech company focused on innovation.
- Benefits: Generous paid leave, private medical cover, and wellbeing resources.
- Other info: Dynamic role with opportunities for leadership and cross-functional collaboration.
- Why this job: Make a real impact by shaping scalable data solutions for major financial institutions.
- Qualifications: 8+ years in ML model development, expert in Python and SQL.
The predicted salary is between 63000 - 77000 £ per year.
As Lead Data Scientist at Cotality, you will steer the technical direction of our predictive modelling efforts and mentor a team of data scientists. You will design and deploy advanced models that power core data products used by major financial institutions, and help shape a scalable data platform. You’ll translate business needs from senior stakeholders into effective analytical solutions, while championing model quality and maintainable production pipelines. This is a high-impact role at a mission-driven fintech-adjacent proptech company, offering hands-on innovation and leadership at scale.
Pay / Benefits
- Generous paid leave
- Up to 16 weeks parental leave
- Private medical cover
- Pension scheme with employer contributions
- Wellbeing and health resources
- Wellbeing allowance
Responsibilities
- Lead design and implementation of advanced predictive models using statistical and ML techniques
- Provide technical leadership and mentorship to data scientists
- Own end-to-end model lifecycle from R&D to production deployment
- Collaborate with senior stakeholders to translate business needs into analytical solutions
- Champion best practices in model development, validation, and maintenance
- Guide technical strategy for core data products and data platform
- Drive innovation and contribute to a culture of excellence
- Partner with Product, Sales, and Leadership to align on insights-based decisions
Key requirements
- 8+ years of experience in developing and deploying high-impact ML models in a commercial environment
- Expert-level knowledge of statistical analysis, predictive modelling, and ensemble techniques (e.g., Gradient Boosted Trees, Random Forests)
- High proficiency in Python (Pandas, Scikit-Learn, XGBoost/LightGBM) and SQL
- Experience with very large, complex datasets; geospatial data experience is advantageous
- Proven ability to mentor and lead technically, guiding complex projects
- Strong communication skills to explain technical concepts to non-technical stakeholders
Lead Data Scientist employer: CoreLogic
Cotality is an exceptional employer that prioritises a diverse and inclusive work culture, fostering innovation and collaboration among its 5,000 global employees. With a remote-first working model, generous benefits including private healthcare, extensive parental leave, and a strong commitment to employee growth, Cotality empowers its team members to thrive both personally and professionally while making a significant impact in the property industry.
StudySmarter Expert Advice🤫
We think this is how you could land Lead Data Scientist
✨Get Involved in Data Science Meetups
Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like CoreLogic!
✨Show Off Your Projects
Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like Lead Data Scientist at CoreLogic.
✨Leverage Professional Networks
Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like CoreLogic.
✨Apply Directly through Our Website
When you find a suitable opening like Lead Data Scientist at CoreLogic, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!
We think you need these skills to ace Lead Data Scientist
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at CoreLogic, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at CoreLogic. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at CoreLogic
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at CoreLogic!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
