Senior Data Scientist (GeoData)

TL;DR

Senior Data Scientist (GeoData): Leading the machine learning model lifecycle for a global ride-hailing platform with an accent on architectural design, MLOps, and scalable data processing pipelines. Focus on translating complex business goals into robust ML systems, mentoring team members, and driving continuous improvement through automation and innovative solutions.

Location: Hybrid role based in Limassol, Cyprus

Company

hirify.global is a global ride-hailing and multi-service tech company operating in 48 countries with a mission to challenge injustice and impact 1 billion lives by 2030.

What you will do

• Lead the end-to-end machine learning model lifecycle from research to production deployment.
• Design and develop scalable ML systems, including data annotation and processing pipelines.
• Contribute to system architecture and integrate ML models with backend services.
• Monitor deployed models to ensure performance and address issues like concept drift.
• Mentor team members and participate in onboarding programs.
• Automate repetitive tasks and drive continuous improvement of ML infrastructure.

Requirements

• Proven experience in a data science or machine learning role.
• Expert-level proficiency in Python and core libraries like Pandas, NumPy, Scikit-learn, and PyTorch.
• Deep expertise in classic machine learning and deep learning techniques.
• Experience with MLOps practices for building, testing, and monitoring production models.
• Strong understanding of software system design and architectural principles.
• Familiarity with streaming, batch, and async data processing technologies.

Nice to have

• Academic background in a quantitative field such as Computer Science or Mathematics.
• Proficiency in specialized domains like NLP, Computer Vision, or Graph Neural Networks.

Culture & Benefits

• Stable salary and official employment.
• Health insurance coverage.
• Flexible work schedule with remote options.
• Access to professional counseling services (psychological, financial, legal).
• Diverse internal training programs and paid additional education.
• Necessary work equipment provided.