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AI Lead Data Scientist in Aviation
2 months ago
zeroG is a pioneering company in the field of AI in Aviation, dedicated to revolutionizing the industry with cutting-edge technology.
We're building a team of exceptional professionals to drive innovation and excellence in our mission to make aviation safer, more efficient, and sustainable.
Our Vision
- To become a leading player in the AI in Aviation industry, known for our innovative solutions and commitment to excellence.
- To create a culture of innovation, collaboration, and continuous learning, where our team members can grow and thrive.
About the Role
We are excited to be hiring a new Lead Data Scientist to join our team in London. As a Lead Data Scientist, you will play a key role in developing and implementing AI solutions that drive business value and improve operational efficiency.
Key Responsibilities
- Develop and lead data science projects that drive business value and improve operational efficiency.
- Collaborate with cross-functional teams to identify business problems and develop data-driven solutions.
- Design and implement machine learning models that improve predictive accuracy and drive business outcomes.
- Work with data engineers to develop and deploy data pipelines and infrastructure.
- Communicate complex technical concepts to non-technical stakeholders and provide data-driven insights to inform business decisions.
Requirements
- Experience with Python and machine learning libraries such as scikit-learn and TensorFlow.
- Strong understanding of data structures, algorithms, and software design patterns.
- Experience with data visualization tools such as Tableau and Power BI.
- Excellent communication and collaboration skills, with the ability to work effectively with cross-functional teams.
- Strong problem-solving skills, with the ability to analyze complex data sets and develop data-driven solutions.
What We Offer
- A competitive salary and benefits package.
- The opportunity to work on cutting-edge AI projects that drive business value and improve operational efficiency.
- A collaborative and dynamic work environment, with a team of exceptional professionals.
- Professional development opportunities, including training and mentorship programs.
Interview Process
- Initial call with Talent Acquisition.
- Hiring Manager Call.
- Take-home task.
- Task debrief and case study interview.
- Final interviews with Head of AI and Head of Data Science.
