Data Science Manager, Aircall
$200-270k
+ Equity
AI-powered communications platform
Job no longer available
AI-powered communications platform
501-1000 employees
Job no longer available
$200-270k
+ Equity
501-1000 employees
Company mission
To empower every professional to have rich conversations, so they can focus on closing deals and delighting customers.
Role
Who you are
- 8+ years of experience in data science, machine learning, or statistical modeling, with a minimum of 3 years in a leadership position
- Proven experience in applying theoretical models to solve real-world problems.M .S. or PhD in Statistics, Computer Science, Mathematics, Operations Research, Physics, or Economics
- Passion for developing data-driven solutions using machine learning and AI.Proficiency in SQL, Python, or other programming languages, as well as statistical/mathematical software
- Strong foundation in statistics, machine learning, operations research, and causal inference. Experience in NLP or Bayesian testing is an advantage
- A natural curiosity and a proactive approach to problem-solving.Demonstrated success in building and leading high-performing data science teams
What the job involves
- The data team is the backbone of Aircall’s decision-making approach. We deliver cutting-edge data products, tools, and actionable insights that drive revenue, profitability, product development, and a delightful customer experience.
- As a Data Science Manager at Aircall, you will be responsible for defining and implementing a comprehensive data strategy that aligns with the company’s strategic goals.
- You will lead initiatives that harness the power of AI, machine learning, and advanced analytics to enhance business operations and drive success.
- You will oversee the full lifecycle of data science projects, from model conception and training to deployment and continuous improvement
- Develop and execute a data strategy that supports Aircall’s business objectives
- Lead innovative projects using AI, machine learning, and data engineering to optimize operational efficiency and drive business growth
- Manage the end-to-end lifecycle of data models, including design, development, deployment, and refinement
- Promote a culture of experimentation by designing and implementing A/B tests to measure the impact of data-driven decisions
- Educate and upskill teams on the latest advancements in AI, ML, and analytics, fostering their application in product development and business processes
- Collaborate with data engineering and AI platform teams to anticipate future requirements and enhance the data infrastructure
- Establish and uphold best practices in data science, analytics, and data engineering, ensuring high standards in data governance and insight generation
- Communicate complex data concepts and insights clearly to stakeholders of varying technical expertise
- Build and maintain strong relationships with stakeholders by addressing their core needs and providing data-driven solutions
Our take
Call centres have been a mainstay of sales teams for decades, with the human touch delivering an impression conversion rate of about 30% for inbound calls. However analogue call centres are physical infrastructure-heavy and unable to take advantage of the flexibility afforded by remote and hybrid ways of work. Aircall exists to change that, providing a cloud-based call centre infrastructure that allows sales teams to work from their home offices.
Aircall isn't the only company in this space, and it faces heavy competition from Cloudtalk, another cloud-based call centre solution. However Aircall stands out in the market by its use of open APIs and webhooks, making integration with existing productivity and helpdesk tools much easier, and its superior call quality. Aircall has developed a significant customer base with these strengths, with over 20,000 companies using its platform.
The company has raised significant funding in recent years, highlighting the confidence investors have in their offering. With a rapidly expanding presence in the US, European, UK and Australian markets and the recent addition of AI voice agents to handle business calls 24/7, Aircall is clearly set on innovating at scale.
Steph
Company Specialist at Welcome to the Jungle
Insights
0% employee growth in 12 months
Company
Funding (last 2 of 6 rounds)
Jun 2021
$120m
SERIES D
May 2020
$65m
SERIES C
Total funding: $225.6m
Company HQ
NoMad, New York, NY
Leadership
Scott Chancellor
(CEO)Prior to joining Aircall as CEO in 2023, Scott was CEO of Humu and Chief Product/Technology Officer at Apptio. He also spent 7 years at Amazon Web Services as a Director and General Manager of AWS Insights.
Salary benchmarks
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