At a Glance
- Tasks: Own data science projects, from predictive models to market analysis and recommendations.
- Company: Join Qogita, a forward-thinking company at the forefront of data-driven decision-making.
- Benefits: Enjoy competitive pay, flexible work options, and opportunities for professional growth.
- Other info: Collaborative environment with cross-functional teams and exciting challenges.
- Why this job: Make a real impact by shaping pricing strategies and understanding market dynamics.
- Qualifications: Strong quantitative skills with a background in economics or finance.
The predicted salary is between 60750 - 74250 £ per year.
You're a data scientist with broad quantitative skills and a background in microeconomics, econometrics, or finance. You'll own data science work across Qogita's business — from forecasting and classification through to experimentation and recommendation systems — and act as the team's go-to on how prices are set, how buyers respond, and how market structure shapes commercial decisions. The Data Science team works cross-functionally with Product, Finance, and Commercial teams to build the analytical and modelling layer that drives Qogita's wholesale marketplace.
Requirements
- Build and deliver data science solutions across the stack — predictive models, segmentation, forecasting, ranking systems, and pricing models — depending on where the business need is greatest.
- Act as the team's domain expert on pricing and market economics: take ownership of the modelling approach, analytical strategy, and how findings translate into commercial recommendations.
- Research, build, deploy and maintain predictive and analytical models that reflect B2B buyer behaviour and wholesale market dynamics.
- Design and analyse experiments and A/B tests, owning statistical validity and translating results into recommendations Product and Commercial can act on.
- Apply a range of quantitative methods — regression modelling, causal inference, ML techniques — to business problems across pricing, demand, market liquidity and beyond.
- Collaborate with Engineers to ship models via reproducible MLOps workflows, including experiment tracking, model serving, and production monitoring.
- Communicate findings and model limitations clearly to Finance, Commercial, and Product stakeholders.
Data Scientist (Economics) in London employer: Qogita
At Qogita, we pride ourselves on being an exceptional employer that fosters a collaborative and innovative work culture. As a Data Scientist in Economics, you'll have the opportunity to work cross-functionally with diverse teams, driving impactful data solutions while benefiting from continuous professional development and a supportive environment. Our commitment to employee growth, coupled with our focus on meaningful projects in the dynamic wholesale marketplace, makes Qogita a rewarding place to advance your career.
StudySmarter Expert Advice🤫
We think this is how you could land Data Scientist (Economics) in London
✨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 Qogita!
✨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 Data Scientist (Economics) at Qogita.
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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 Qogita.
✨Apply Directly through Our Website
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We think you need these skills to ace Data Scientist (Economics) 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 Qogita, 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 Qogita. 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 Qogita
✨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 Qogita!
✨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.
