Principal data scientist - Bay Area -

June 19

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Aircall

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The phone system for modern business

Call center software • VoIP • Cloud • Business phone system • Customer Support

501 - 1000

💰 Venture Round on 2022-02

Description

• Aircall is seeking a visionary Principal Data Scientist to establish and drive initiatives whose ambition is to impact our processes leveraging applied data science. • This is a unique opportunity to play a pivotal role in shaping our scientific foundation. You will leverage data and advanced ML/AI/Generative AI techniques to optimize operations across various domains, including marketing, fraud prevention, and call quality. Leading impactful initiatives such as Marketing Mix Modeling and churn prediction, you will oversee the entire lifecycle from ideation to production and continuous improvement. Expect to have both the freedom and responsibility to define goals, build and grow a team, and make a significant impact at Aircall. • Locations: Paris, Bay Area (USA), or NYC HQ

Requirements

• 6+ years of data science, machine learning / statistical modeling experience • Experience implementing theoretical models in an applied environment • M.S. or PhD. in Statistics, Computer Science, Math, Operations Research, Physics, Economics, or other quantitative field • Strong interest in delivering data-driven solutions using ML and AI • Proficiency in data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software • Solid understanding of statistics, machine learning, operations research, and causal inference. Knowledge of NLP or Bayesian testing is a plus • Insatiable curiosity and bias toward action

Benefits

• Lead groundbreaking projects that leverage AI and machine learning techniques to optimize operations and drive business success • Take ownership of the entire lifecycle from model design, training, productionization and incremental enhancement • Foster a culture of experimentation by designing and scale rigorous A/B tests when needed to measure business impact • Educate internal analytics teams on current and emerging research, technologies, and best practices for leveraging ML and LLM in product design and development • Collaborate with AI Platform engineers to identify upcoming requirements and continuously evolve the AI platform offering • Establish best practices in data science and mentor future team members to maintain high standards in data governance and insight generation • Communicate effectively with stakeholders across various technical levels, articulating insights and recommendations about your solutions • Cultivate trust with stakeholders by consistently addressing their true fundamental needs and challenges