About the role The Data Engineering team at Aircall works on providing high-quality, reliable, and actionable data. As an AI-first data team, we are currently in a pivotal transition to build a robust semantic layer that will power our AI-first data platform, enabling analytics at speed and democratizing intelligent insights across the company. Some of the key problems we are currently solving include taking charge of data reliability, integrating new sources for raw data ingestion, and building sophisticated data models to power real-time dashboards and predictive analytics. In this role, you will be instrumental in building new datasets for high-impact use cases such as churn prediction and feature adoption, while owning the end-to-end reliability and scalability of our data pipelines. You will work closely with Product and GTM business teams, sitting at the heart of a larger data organization alongside Data Science, Analytics, and Applied Scientists to bridge the gap between raw data and AI-driven decision-making.
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Remote role · data-sci
Data Scientist
Aircall
Salary$140k - $180k
Before you apply
The practical pictureRole details
- Employment
- Full-time
Role signal brief
The role, at a glance
Extracted from the source posting · 95% confidence
Aircall is hiring a Data Scientist to join its AI-first data engineering team in a hybrid role at its New York office. The candidate will own end-to-end data pipeline reliability and build new datasets for high-impact use cases like churn prediction, while partnering with GTM stakeholders to translate business questions into scalable data products.
- Compensation
- USD 140,000–180,000 / year
What you need
- 2+ years of hands-on experience in a high growth environment
- Proficiency in SQL for deriving insights
- Proficiency in Python
- Hands-on Looker/LookML experience
- Excellent interpersonal skills and the ability to explain complex data clearly to stakeholders at all levels
- You have an insatiable curiosity and are biased toward action
What you will own
- Partner with GTM stakeholders to translate business questions into reliable, scalable data products.
- Provide actionable insights and compelling narratives to influence major decisions at the C-level.
- Build and own reporting in Looker, from LookML development to dashboard performance optimization, powering self-service analytics GTM teams rely on every day.
- Work closely with data engineers to continuously improve the data stack, governance practices, and analysis quality.
Core skills
SQLPythonLooker/LookMLData AnalysisStakeholder CommunicationChurn PredictionData Pipeline ReliabilityDashboard Optimization
Role brief
About the role The Data Engineering team at Aircall works on providing high-quality, reliable, and actionable data. As an AI-first data team, we are currently in a pivotal transition to build a robust semantic layer that will power our AI-first data platform, enabling analytics at speed and democratizing intelligent insights across the company. Some of the key problems we are currently solving include taking charge of data reliability, integrating new sources for raw data ingestion, and building sophisticated data models to power real-time dashboards and predictive analytics. In this role, you will be instrumental in building new datasets for high-impact use cases such as churn prediction and feature adoption, while owning the end-to-end reliability and scalability of our data pipelines. You will work closely with Product and GTM business teams, sitting at the heart of a larger data organization alongside Data Science, Analytics, and Applied Scientists to bridge the gap between raw data and AI-driven decision-making.