In a world where many social apps measure their success by time spent online, Places offers a different kind of product built by Raya, a technology company focused on providing utility. Our apps, Raya and Places, are tools for discovery of and access to exciting people and places globally. We believe that by marrying great software with a membership-based community built around core values of trust, curation, and authenticity, we can provide solutions that offer something different to infinite content and AI-slop. Placesโ mission is to help discerning global travelers find their favorite places wherever they go through expert curation and community trust.
As a Data Scientist on the Places by Raya team you will play a key role that will shape how the Places app uses data to drive business decisions. This hands-on role combines data modeling and reporting with product analysis and experimentation. While the product itself has existed since 2023 the culture is very much like a new start-up with leadership being heavily invested in this product space and this role being the first dedicated Data Scientist to this space and supported by a dedicated Data Engineer.
We are seeking an entrepreneurial and driven data scientist to identify opportunities to improve retention and help the team evaluate and act on them. This will be a fun role for someone who wants to build data solutions from the ground up and help shape how the entire team uses insights. This person should be able to articulate best practices, develop new analytical frameworks that tie user actions to outcomes, and strike the right balance between analytical rigor and pragmatic business action.
Successful candidates will demonstrate technical skills, product expertise, and business acumen, and be enthusiastic about making a positive impact through timely execution. You are passionate about leveraging the power of data to drive product changes with quality and agility and can demonstrate sound judgment under uncertainty.
Responsibilities
Own the definition and evolution of success metrics for all user facing surfaces, including tradeoffs between short-term and long-term member value.
Define and maintain business metrics, semantic layers, and data models to ensure consistency and trust across the Places team.
Own, in partnership with Data Engineering, the translation of product requirements into scalable, reliable data assets that empower efficient decision-making
Influence product direction by uncovering and translating insights into clear recommendations that shape roadmap prioritization.
Build out a culture of high fidelity experimentation to scale wins quickly
Using visualisations to convey nuance with clarity
AI-native mindset and hands-on experience using LLMs, agents, and modern AI tools to automate analysis, accelerate experimentation, and build scalable decision-support workflows
Qualifications
5+ years of data science and product analytics experience
BS and/or MS in a quantitative discipline: statistics, operations research, computer science, engineering, applied mathematics, physics, economics, etc.
Familiarity in delivering data products through partnership with Data and product engineering teams.
Strong technical fluency with analytical tools such as SQL and Python, or equivalent experience using data to answer open-ended business questions.
Strong applied statistics background, including hypothesis testing, confidence intervals, power analysis, and causal inference techniques.
Familiarity with modern analytics and experimentation tools
Familiarity with consumer focused .
Strong in proactive verbal and written communication, ability to convey rigorous statistical concepts to non-experts.
Practical AI fluency and curiosity about how modern AI tools can improve analytical workflows, strategic synthesis, and decision support.
Bonus points for familiarity with optimization of performance marketing efforts
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
