Lead Data Scientist- Recommendation Systems

Tiger Analytics is looking for experienced Data Scientists to join our fast-growing advanced analytics consulting firm. Our consultants bring deep expertise in Data Science, Machine Learning and AI. We are the trusted analytics partner for multiple Fortune 500 companies, enabling them to generate business value from data. Our business value and leadership has been recognized by various market research firms, including Forrester and Gartner. We are looking for top-notch talent as we continue to build the best global analytics consulting team in the world.

We are also market leaders in AI and analytics consulting in the CPG & retail industry with over 40% of our revenues coming from the sector. This is our fastest-growing sector, and we are beefing up our talent in the space.

We are seeking a highly skilled and experienced Lead Data Scientist with a strong background in Recommendation Systems and Machine Learning Engineering (MLE). The ideal candidate will have a proven track record in designing, implementing, and deploying large-scale recommendation solutions, while also leading projects and mentoring teams. This role requires technical depth, hands-on coding, and the ability to engage directly with clients and stakeholders .

Key Responsibilities

• Design, develop, and optimize end-to-end recommendation systems, from data ingestion to model deployment.
• Build, fine-tune, and evaluate recommendation algorithms for scalability and performance.
• Collaborate with engineering and product teams to integrate ML solutions into business applications.
• Lead and manage projects, ensuring timely delivery of solutions aligned with business objectives.
• Provide technical guidance and mentorship to junior data scientists and engineers.
• Work directly with clients and stakeholders, demonstrating strong communication and problem-solving skills.
• Drive innovation by exploring and implementing new techniques in recommendation systems and Al.
• Stay abreast of industry trends and best practices in data science, replenishment optimization, and supply chain management, and leverage this knowledge to drive innovation within the organization.
• Collaborate, coach, and learn with a growing team of experienced Data Scientists.