Senior Data Scientist: LTV, Bidding & Fraud Modeling

Senior Data Scientist: LTV, Bidding & Fraud Modeling

Full-Time 60750 - 74250 £ / year (est.) No working from home possible
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At a Glance

  • Tasks: Own end-to-end models for user valuation and monetisation decisions.
  • Company: Fast-growing adtech startup in the UK with a dynamic culture.
  • Benefits: Competitive salary, flexible working hours, and opportunities for professional growth.
  • Other info: Join a small, autonomous team and make a real impact.
  • Why this job: Shape the future of data science while driving revenue growth and fraud protection.
  • Qualifications: Experience in data science, modelling, and collaboration with engineering teams.

The predicted salary is between 60750 - 74250 £ per year.

Scrambly, a fast-growing adtech startup in the UK, seeks a Senior Data Scientist to own end-to-end models for valuing users and guiding monetisation decisions. You will forecast user value, set pricing controls, and collaborate with engineers to deploy reliable data-driven solutions that support revenue growth and fraud protection.

You will work closely with the Head of Data in a small, autonomous team, shaping the direction of data science at Scrambly and translating complex models into actionable insights.

Senior Data Scientist: LTV, Bidding & Fraud Modeling employer: Scrambly

At Scrambly, we pride ourselves on being an exceptional employer that fosters a collaborative and innovative work culture. As a Senior Backend Engineer, you will not only tackle high-scale challenges but also have ample opportunities for professional growth and mentorship within a dynamic team. Located in a vibrant tech hub, we offer competitive benefits and a supportive environment that encourages creativity and excellence in delivering scalable solutions for millions of users worldwide.

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Contact Details:

Scrambly Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land Senior Data Scientist: LTV, Bidding & Fraud Modeling

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Apply Directly through Our Website

When you find a suitable opening like Senior Data Scientist: LTV, Bidding & Fraud Modeling at Scrambly, 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 Senior Data Scientist: LTV, Bidding & Fraud Modeling

Data Modelling
User Valuation
Monetisation Strategies
Forecasting
Pricing Controls
Collaboration with Engineers
Data-Driven Solutions

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 Scrambly, 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 Scrambly. 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 Scrambly

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 Scrambly!

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.