At a Glance
- Tasks: Transform customer data into actionable insights for marketing strategies and business growth.
- Company: Established analytics and technology firm with a focus on innovation.
- Benefits: Competitive salary, flexible work arrangements, and opportunities for professional development.
- Other info: Dynamic role with opportunities to own projects and collaborate across various sectors.
- Why this job: Make a real impact by shaping marketing strategies for major brands using data science.
- Qualifications: Experience in Python, SQL, and customer modelling with strong statistical foundations.
The predicted salary is between 60750 - 74250 £ per year.
Senior Data Scientist | Customer Modelling & Marketing Up to 75,000 Dependent on experience London | Office Monday - Thursday, Friday work from home Job reference: Have you built customer segments that shaped a marketing strategy?
An established analytics and technology business is looking for a hands-on Senior Data Scientist to turn first-party customer data into practical tools for acquisition, retention and growth.
You'll work across established products and new developments, helping major brands make better decisions and measure the commercial impact of your models.
What you'll do·Develop customer segments using behavioural and transactional data, helping businesses understand their customers and take targeted action.·Work with large customer datasets spanning multiple years, owning data preparation, feature engineering and model evaluation.·Partner with marketing and CRM teams to activate model outputs in campaigns and measure their impact.·Take models through to production with engineering colleagues, monitoring performance and improving them over time.·What you'll bring You'll be actively building models in Python and SQL, with examples you can explain from the original business question through to implementation and results.
We're particularly interested in experience of:·First-party customer data: personally modelling customer behaviour and transactions, rather than working solely with aggregated reporting.·Segmentation you designed: selecting the approach, validating the segments and helping the business use them.·Predictive modelling: building and evaluating propensity, churn, value or forecasting models.·Marketing activation: putting scores, segments or predictions into CRM journeys or campaigns and assessing the outcome.·You'll bring strong statistical foundations, sound commercial judgement and the confidence to discuss technical choices and trade-offs.
Experience in retail, insurance, financial services or subscription businesses is helpful, but relevant customer-modelling experience matters more than sector.
Work across different brands, datasets and commercial challenges.·Own projects from the initial question through to production and measured outcomes.·This vacancy cannot accommodate Graduate/Post Study or Skilled Worker visa arrangements.
Senior Data Scientist - AI in London employer: Datatech Analytics
Datatech Analytics is an exceptional employer located in the vibrant City of London, offering a dynamic work culture that fosters collaboration and innovation. As a Trading Operations Graduate Analyst, you will benefit from comprehensive training and mentorship, ensuring your professional growth while working alongside industry experts in a fast-paced environment. With a commitment to employee well-being and a focus on meaningful contributions to global trading operations, Datatech Analytics provides a rewarding career path for ambitious graduates.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Data Scientist - AI in London
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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 Datatech Analytics.
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We think you need these skills to ace Senior Data Scientist - AI in London
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 Datatech Analytics, 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 Datatech Analytics. 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 Datatech Analytics
✨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 Datatech Analytics!
✨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.
