About the Company

A leading Azerbaijan-based technology ecosystem operating across fintech, digital payments, and e-commerce sectors. The company is focused on building innovative, data-driven products and delivering large-scale AI solutions that impact millions of users and businesses across the region.

Position Overview

We are seeking an experienced Senior AI & Data Scientist to lead the design, development, and deployment of advanced AI and Machine Learning solutions. This role offers the opportunity to work on high-impact projects, leverage cutting-edge technologies, and drive innovation across a rapidly growing digital ecosystem.

Please note: this position is based in Baku, Azerbaijan, and requires relocation for candidates currently residing outside the country.

Key Responsibilities

• Lead AI and Machine Learning initiatives from business problem definition through production deployment.
• Design, develop, and optimize advanced machine learning and AI models for real-world applications.
• Work with large and complex datasets to build scalable, high-performance solutions.
• Conduct in-depth data analysis to identify business opportunities, trends, and risks.
• Collaborate closely with Data Engineers, ML Engineers, Product Managers, and business stakeholders.
• Establish and promote best practices in model governance, monitoring, and continuous improvement.
• Enhance and maintain existing AI models, pipelines, and analytical tools.
• Mentor and support junior and mid-level Data Scientists.
• Stay up to date with emerging AI technologies and proactively introduce innovative approaches.

Requirements

• Master’s degree in Computer Science, Data Science, Statistics, Mathematics, or a related field.
• 5+ years of hands-on experience in Data Science, Machine Learning, or Applied AI.
• Strong programming skills in Python and experience with machine learning, deep learning, and data processing frameworks.
• Deep understanding of machine learning algorithms, deep learning techniques, model optimization, and evaluation methodologies.
• Practical experience with NLP, Large Language Models (LLMs), Generative AI, Prompt Engineering, RAG architectures, Embeddings, Vector Databases, recommender systems, and predictive analytics.
• Experience building and maintaining end-to-end machine learning pipelines.
• Strong knowledge of MLOps practices, including model versioning, monitoring, and lifecycle management.
• Ability to communicate complex technical concepts to both technical and non-technical stakeholders.
• Strong leadership, collaboration, and mentoring skills.
• Experience guiding or mentoring junior team members is highly desirable.