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Lead Data Scientist - Banking


Job details
  • CAVU
  • Manchester
  • 1 day ago

Lead Data Scientist Manchester – Hybrid Permanent For airports, for partners, for people. Formed from the union of MAGO, MAG USA, and a network of direct-to-consumer brands, we deliver market-leading passenger experiences and drive profitable results for airports worldwide. From Propel, our revenue-accelerating single platform technology, to our world-class hospitality venues, including Hangar, 1903, and Escape Lounges, our solutions streamline travel and boost revenue. Inspired by the aviation term “Ceiling and Visibility Unlimited,” CAVU embodies our vision of creating seamless, enjoyable travel experiences for airport passengers. The Lead Data Scientist will be instrumental in designing advanced data analytics, machine learning models, and predictive insights to support the entire organisation, from Trading to Digital Marketing, and Customer & Travel Product Development. Working closely with the Data Team and key business stakeholders, you’ll navigate a dynamic business landscape driven by acquisitions, integrations, and digital transformation. You’ll be a seasoned data science professional with strong expertise in machine learning and statistical analysis, comfortable leading complex data projects and mentoring a team. You’re passionate about driving insights that shape strategic decisions, enhance our competitive edge, and support our mission of redefining travel. Team Leadership: Lead, mentor, and manage a team of data scientists and analysts, fostering a collaborative culture focused on innovation and continuous growth. Data Strategy Development: Define and execute CAVU’s data science strategy in alignment with business goals, focusing on M&A activities and leveraging data to drive impactful solutions. - Coordinate with IT and data engineering teams to ensure a robust data infrastructure. - Project Management: Oversee data science projects from inception to completion, prioritizing based on business impact and resource availability, and ensuring timely delivery of high-quality solutions. - Data Analysis & Modelling: Conduct advanced data analysis and modelling to identify patterns and trends, develop predictive models, and optimise business processes. Translate complex data into actionable insights. As Lead Data Scientist, you will drive strategic decision-making for the Data Team, applying best practices in advanced data modelling and stakeholder engagement. Your insights will directly influence business strategy, optimise data usage, and ensure the scalability and efficiency of our data science solutions. Data Science & Statistical Expertise: Extensive experience with Python, SQL, and complex data analysis. Proven success in collaborating with Data Engineering to optimise data infrastructure. - Machine Learning Proficiency: Strong knowledge of machine learning, data mining techniques, and predictive analytics, particularly in GBMs, neural networks, and large language models (LLMs). - Advanced ML Tools: Hands-on experience with machine learning libraries and platforms like Amazon SageMaker, TensorFlow, and PyTorch. - Project Management & Agile Methodologies: Experienced in Agile or Kanban frameworks, with a track record of managing projects in tools like Jira and Confluence. - Artificial Intelligence Implementation: Experience implementing AI solutions to enhance business processes and address unique business challenges (preferred). - Attention to Detail: High accuracy and quality standards in deliverables. This is a unique opportunity to lead a data science team in a high-growth, innovative environment with significant autonomy. As CAVU continues its growth, there are endless opportunities for future career development. 25 Days Holiday with the option to buy up to 10 more, plus 4 flexible bank holidays - 10% Company Pension - Annual Bonus Scheme - On-Site Gym - Flexible Benefits & Discounts We are an equal opportunities employer, valuing diversity in all its forms. We also provide reasonable accommodations to ensure everyone can participate fully in our hiring process.

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