Head of Data Science

At Quicklizard, we're transforming the way retailers make pricing decisions through AI, machine learning, and advanced analytics. Our platform empowers global retailers and brands to optimize pricing, increase profitability, and respond to market changes in real time.

We're looking for a Head of Data Science to lead our Data Science function and drive the evolution of our AI-powered pricing optimization platform. This is a unique opportunity to combine strategic leadership with hands-on innovation, working closely with Product, R&D, Customer Success, and executive leadership to shape the future of our technology.

Responsibilities

• Lead and mentor a global team of Data Scientists

• Define and execute the company's Data Science strategy

• Drive the development of advanced machine learning, optimization, and forecasting solutions

• Partner closely with Product, Engineering, Customer Success, and executive leadership

• Translate complex business challenges into scalable analytical solutions

• Support customer-facing initiatives and strategic engagements when needed

• Establish best practices for experimentation, model evaluation, and performance measurement

• Act as a key stakeholder in shaping the company's AI vision and roadmap

Requirements

• 8+ years of experience in Data Science, Machine Learning, Statistics, Operations Research, Economics, or a related field

• Proven experience leading Data Science teams

• M.Sc. or Ph.D. in a quantitative discipline

• Strong expertise in machine learning, predictive analytics, optimization, forecasting, and statistical modeling

• Experience in fintech, revenue optimization, forecasting, recommendation systems, retail technology, or similar data-intensive domains

• Strong business orientation and ability to connect analytical insights to business outcomes

• Excellent communication and stakeholder management skills

• Experience working in a SaaS environment

• Fluent English

Advantage

• Experience with Generative AI and LLM-based applications

• Experience working with enterprise customers

• Experience managing distributed teams