Peatix is looking for a Data Scientist to join our strategy team. This role offers you an exciting and meaningful opportunity to shape the future of the company and product, as we redefine how people can connect with one another through shared experiences.
The mission of the Data Scientist is to maximize “cross-side” network effects. More specifically, you aim to increase and improve interactions between event organizers who want to sell tickets and people who want to attend events, and to maximize the satisfaction of both parties. You will be responsible for algorithm development and evaluation of various products, such as personalization, optimization of in-platform advertisement and email, search and so on. Data analysis is also an important part of the role to gain insight and deep understanding of users and clients.
To be successful in this role, knowledge of data science is important, as well as working with the product manager to understand stakeholders’ needs and problems, working with engineers to release products, and having the creativity to solve problems.
- Contribute to the design, testing, and iteration of the machine learning algorithms that form the backbone of Peatix products
- Create and improve predictive models (e.g. ticket sales or user churn)
- Analyze data to inform strategy and product/UX changes for user onboarding, engagement, retention, and monetization
- Work closely with product managers, designers, and engineers to conduct A/B tests and iterate on better product improvements
- Develop deep domain expertise about event and community
- Work with our data warehousing systems to design, build, and maintain analyses and performance visualizations for users, major product initiatives, and other internal needs
- Bachelors or higher degree in Statistics, Computer Science, Economics, Operations Research or similar quantitative field, or 3+ years of practical machine learning experience
- Experience of developing productionized machine learning systems, such as Recommender, Search etc
- Programming proficiency (preferably Python, its data science stack, and SQL) and desire to write production code
- Intermediate knowledge of applied statistics ( hypothesis testing, fit regression curves, build predictive models, choose sample sizes, etc.)
Nice to haves
These aren’t required, but be sure to mention them in your application if you have them.
- An M.S. or PhD in Statistics, Computer Science, Economics, Operations Research or similar quantitative field
- Experience with / working in one of the following fields: reinforcement learning, deep learning or Natural language processing (NLP)
- Comfortable with using git, docker, and other tools for writing robust, production-ready code
- Conversational level Japanese or above