Data Scientist (AI)

TL;DR

Data Scientist (AI): Developing advanced predictive models and scalable data solutions to drive business strategy with an accent on machine learning, statistical analysis, and Microsoft Fabric integration. Focus on transforming complex data into actionable insights for customer acquisition, retention, and margin optimization.

Location: Must be based in or able to commute to Leeds, UK (Hybrid: 1-2 days/week on-site)

Company

hirify.global is a fleet solutions provider supporting over 55,000 customers nationwide with a focus on innovation and collaborative growth.

What you will do

• Partner with stakeholders to identify business opportunities and develop data science roadmaps.
• Design, deploy, and improve predictive, propensity, and optimization models.
• Contribute to the transition and adoption of the Microsoft Fabric data platform.
• Collaborate with Data Engineering to integrate internal and external data sources.
• Communicate insights through intuitive dashboards and data products for technical and non-technical stakeholders.
• Promote a data-driven culture by applying advanced analytics and AI to solve business problems.

Requirements

• Proven experience as a Data Scientist or in a similar analytical role.
• Strong proficiency in Python, R, and SQL.
• Solid understanding of statistical analysis, machine learning, and optimization algorithms.
• Experience working within Agile Scrum teams.
• Degree or higher education qualification in a relevant field.
• Must be able to work on-site in Leeds, UK, 1-2 days per week.

Nice to have

• Experience within the fleet industry.
• Experience with Microsoft Fabric and modern lakehouse architectures.
• Proficiency in data visualization tools like Qlik or Power BI.

Culture & Benefits

• Hybrid working model with 1-2 days in the Leeds office.
• 25 days annual leave plus bank holidays and a birthday day off.
• 10% annual bonus scheme.
• Pension plan and 4x salary life assurance.
• Additional perks including free breakfast, cycle to work scheme, and early Friday finishes.