At a Glance
- Tasks: Design and improve dynamic pricing policies using data science and real-time algorithms.
- Company: Join an innovative company committed to fair choices for millions globally.
- Benefits: Access to mentoring, career consulting, and global exchange programs.
- Other info: Engage in social impact projects and enhance your language skills.
- Why this job: Make a real impact on pricing systems while developing your professional skills.
- Qualifications: Experience in Data Science, Python, SQL, and algorithmic product optimisation.
The predicted salary is between 63000 - 77000 £ per year.
Put your data science role in front of the right audience.
Key Responsibilities:
- Design and improve dynamic pricing policies, including elasticity and supply/demand response modeling.
- Frame pricing as a decision system under uncertainty and delayed feedback.
- Develop, test, and deploy a real-time pricing algorithm.
- Design and analyze A/B experiments to evaluate pricing impact.
- Productionize models in collaboration with engineering, ensuring scalability and robustness.
- Monitor system performance, including stability, feedback effects, and long-term behavior.
- Contribute to methodological choices (e.g., optimization, control, reinforcement learning-inspired approaches).
Skills, Knowledge and Expertise:
- Professional experience in Data Science, Applied Research, or algorithmic product optimization, preferably in marketplaces or pricing systems.
- Strong background in statistics, optimization, and causal inference.
- Proven ability to move from problem formulation to production-grade solution.
- Proficiency in Python, SQL, and experience with production ML systems.
Nice to Have:
- Experience with economic modeling (elasticity, auctions, policy design).
- Familiarity with control systems, reinforcement learning, or online optimization.
- Experience working with real-time, high-load systems.
Help us challenge injustice by creating fair choices for millions of people across 1100+ cities in 47 countries. Develop your professional skills with access to mentoring, career consulting, and learning programs. Collaborate with teams around the world and gain international experience through our Global Talent Exchange Program. Engage in company-wide challenges, awards, sports activities, employee-led social impact and volunteering projects. Work alongside people who take initiative, speak openly, and challenge themselves to grow. Improve your language skills through co-financed courses and internal speaking clubs.
Final benefits may vary depending on the location.
Lead Applied Researcher — Dynamic Pricing employer: inDrive
inDrive is an exceptional employer that fosters a collaborative and innovative work culture, making it an ideal place for a Senior DevOps Engineer to thrive. With a focus on employee growth, you will have access to continuous learning opportunities and the chance to work on cutting-edge technology in the vibrant UK tech scene. Enjoy the unique advantage of being part of a global team that values your contributions and encourages a healthy work-life balance.
StudySmarter Expert Advice🤫
We think this is how you could land Lead Applied Researcher — Dynamic Pricing
✨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 inDrive!
✨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 Applied Researcher — Dynamic Pricing at inDrive.
✨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 inDrive.
✨Apply Directly through Our Website
When you find a suitable opening like Lead Applied Researcher — Dynamic Pricing at inDrive, 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 Applied Researcher — Dynamic Pricing
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 inDrive, 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 inDrive. 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 inDrive
✨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 inDrive!
✨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.
