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For Companies At a Glance
- Tasks: Analyse complex datasets and build machine learning models to drive economic insights.
- Company: Join Oxford Economics, a leader in economic forecasting and consulting.
- Benefits: Enjoy private healthcare, flexible working, and enhanced parental leave.
- Why this job: Make a real impact by applying your data skills in a dynamic environment.
- Qualifications: 2-5 years in data science or applied economics with strong programming skills.
- Other info: Collaborative culture with opportunities for professional growth and innovation.
The predicted salary is between 28800 - 48000 £ per year.
Oxford Economics, a leading economic forecasting and consulting firm, is seeking a senior data scientist to join its Economic Impact team. The successful candidate will report into the team lead and play a key role in delivering high‑quality economic analysis and driving analytical and technical capability across the team.
Key Responsibilities
- Applying quantitative techniques to large complex datasets using R and/or Python
- Design, build and deploy econometric and machine learning models for clients across the consultancy business
- Communicating with clients effectively, responding promptly and positively to their enquiries, with progression to handling and developing client relationships
- Working with colleagues to develop research proposals and project reports
- Being able to plan and structure your own project work, ensuring sufficient time for quality assurance from senior colleagues
- Taking the initiative in suggesting ways to strengthen the quality of our analysis through creative solutions
- Taking the lead on technical aspects of project work, with progression to managing projects
Skills, Knowledge & Expertise Required
- 2-5 years’ professional experience in data science or applied economics
- Familiarity working with at least one cloud platform provider (e.g AWS, GCP, Azure)
- Experience working in a collaborative environment using version control software (e.g Git)
- Experience building and deploying machine learning models (supervised, unsupervised, and/or deep‑learning models)
- Familiarity with modern generative AI concepts (e.g embeddings, RAG pipelines, fine‑tuning)
- Strong programming skills in Python; desirable to have at least one other such as R, SQL, JavaScript, etc.
- Experience working with a variety of structured and unstructured data
- Excellent written and verbal communication, including the ability to explain economic concepts and quantitative results to non‑specialists
- Experience building UI dashboards to visualise and engage with complicated data (e.g. Streamlit, PowerBI, etc.)
- An understanding of using containerised workflows (e.g Docker)
Desired
- A postgraduate degree in economics or a closely related quantitative discipline
- Experience conducting economic analyses using large complex datasets, for example company procurement databases, survey microdata, Bloomberg, etc.
- Experience working with a deep‑learning framework such as PyTorch or TensorFlow
Job Benefits
- Private Healthcare
- Employee Assistance Program
- Enhanced Maternity and Paternity Leave
- Workplace Nursery Scheme
- Cycle to Work Scheme
- Hybrid/Flexible Working
- Team Gatherings and Connection Boost!
Equal Employment Opportunity (EEO)
Oxford Economics is an equal opportunity employer that is committed to diversity and inclusion in the workplace. We prohibit discrimination and harassment of any kind based on race, color, sex, religion, sexual orientation, national origin, disability, genetic information, pregnancy, or any other protected characteristic as outlined by federal, state, or local laws.
(Sr.) Economist / Data Scientist - Economic Impact - London employer: Oxford Economics
Contact Detail:
Oxford Economics Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land (Sr.) Economist / Data Scientist - Economic Impact - London
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend events, and connect on LinkedIn. You never know who might have the inside scoop on job openings or can put in a good word for you.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving R, Python, or machine learning models. This will give potential employers a taste of what you can do and set you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on your communication skills. Practice explaining complex economic concepts in simple terms, as you'll need to engage with clients and colleagues alike. We want you to shine!
✨Tip Number 4
Don't forget to apply through our website! It’s the best way to ensure your application gets noticed. Plus, it shows you're genuinely interested in joining our team at Oxford Economics.
We think you need these skills to ace (Sr.) Economist / Data Scientist - Economic Impact - London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the role of (Sr.) Economist / Data Scientist. Highlight your experience with data analysis, machine learning models, and any relevant programming skills. We want to see how your background fits perfectly with what we're looking for!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about economic impact and how your skills can contribute to our team. Keep it engaging and personal – we love to see your personality come through!
Showcase Your Projects: If you've worked on any relevant projects, make sure to mention them! Whether it's building machine learning models or creating dashboards, we want to know what you've done. Include links to your work if possible – it really helps us get a sense of your capabilities.
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way to ensure your application gets to us without any hiccups. Plus, it shows you're keen on joining our team at StudySmarter!
How to prepare for a job interview at Oxford Economics
✨Know Your Data Inside Out
Make sure you’re well-versed in the datasets you’ll be working with. Brush up on your experience with large complex datasets and be ready to discuss specific examples of how you've applied quantitative techniques using R or Python.
✨Showcase Your Technical Skills
Prepare to demonstrate your programming prowess, especially in Python. Be ready to talk about any machine learning models you've built or deployed, and if you have experience with cloud platforms like AWS or GCP, make sure to highlight that too!
✨Communicate Clearly and Confidently
Since you'll be communicating with clients, practice explaining complex economic concepts in simple terms. Think of examples where you’ve successfully conveyed technical information to non-specialists, as this will show your ability to bridge the gap between data and decision-making.
✨Be Proactive and Solution-Oriented
During the interview, don’t hesitate to suggest creative solutions or improvements based on your past experiences. This shows initiative and a willingness to contribute positively to the team’s analytical capabilities.
