Senior Data Scientist, Investment Modeling
vor 3 Wochen
We are looking for an experienced Data Scientist to join our Investment Modeling team to build quantitative growth models and optimise investments across hundreds of cities around the world
About us
Bolt is one of the fastest-growing tech companies in Europe and Africa, with over 150 million customers in 45+ countries. We're a global team of more than 100 nationalities joined on a common mission – to make cities for people, not cars. And we need you to make it happen
About the roleYou will be building forecasting models to predict the short and long-term impact of incentives on growth of the business. You will use an optimization techniques to distribute incentives over time periods, across different cities and channels to maximize the growth of the business. As a Data Scientist you will be building products powered by Data Science models for internal teams to use in portfolio planning and budgeting. In addition you will work on decomposing and modeling business growth by interpretable and actionable components
Your daily adventures will include:
- Develop a deep understanding of technical and business needs to solve real-world problems end-to-end
- Research, test and apply novel forecasting techniques and methods
- Develop and maintain predictive models to ensure accurate forecasts at short and long horizons for multiple business verticals
- Quickly deploy models to production using AWS and internal machine learning platform
- Solve optimization problems for incentives budget allocation within local and global constraints.
- Communicate and present results to product and business stakeholders
- Work with Python, Spark, Presto, Docker, SageMaker, Airflow
- Work with data analysts, data scientists, product managers and software engineers in cross-functional feature teams
- Regularly exchange knowledge with Data Scientists at various levels of seniority in the company
- Industry experience in data science and machine learning (3+ years recommended)
- Natural curiosity to identify problems, explore trends and discover opportunities with little supervision
- Capability to approach problems with first principles thinking
- Team player with strong verbal and written communication skills in English
- Experience in time series analysis, modeling multivariate time series, familiarity with forecasting techniques
- Experience in Python programming, including libraries like Pandas, Numpy, sklearn, OR-tools
- Understanding and practical experience with statistical hypothesis testing
- You will get extra credits for product development experience in a technology company
- You will get extra credits for Ph.D in a quantitative field (physics, mathematics, computer science, economics)
- You will get extra credits for an experience with multivariate time series forecasting methods
Experience is great, but what we really look for is drive, intelligence, and integrity. So even if you don't tick every box, please consider applying if you feel you're the kind of person described above
- Play a direct role in shaping the future of mobility.
- Impact millions of customers and partners in 500+ cities across 45 countries.
- Work in fast-moving autonomous teams with some of the smartest people in the world.
- Accelerate your professional growth with unique career opportunities.
- Get a rewarding salary and stock option package that lets you focus on doing your best work.
- Enjoy the flexibility of working in a hybrid mode.
- Take care of your physical and mental health with our wellness perks.
*Some perks may differ depending on your location.
#LI-Hybrid
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Senior Data Scientist, Investment Modeling
vor 3 Wochen
Berlin, Berlin, Deutschland Bolt Technology VollzeitWe are looking for an experienced Data Scientist to join our Investment Modeling team to build quantitative growth models and optimise investments across hundreds of cities around the world About us Bolt is one of the fastest-growing tech companies in Europe and Africa, with over 150 million customers in 45+ countries. We're a global team of more than 100...
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