Lead Data Scientist (Client Acquisition)

TL;DR

Lead Data Scientist (Client Acquisition): Driving data-driven strategies for client onboarding, engagement, retention, and personalization with an accent on predictive modeling and behavioral analytics. Focus on optimizing user experiences and translating complex data into actionable business decisions.

Location: Hybrid role based in Limassol, Athens, or Nicosia, in Cyprus or Greece.

Company

hirify.global is seeking a Lead Data Scientist with expertise in behavioral analytics to drive data-driven strategies for client acquisition, engagement, retention, and personalization.

What you will do

• Utilize advanced analytics and predictive modeling to drive client acquisition strategies.
• Optimize client onboarding and segmentation by analyzing user behavior.
• Build predictive models for churn and design personalized recommendation systems.
• Implement machine learning and AI techniques to extract meaningful insights from client behavior data.
• Design, execute, and analyze A/B tests to optimize processes and decision-making.
• Mentor and guide data science teams, fostering innovation and technical excellence, and present insights to non-technical stakeholders.

Requirements

• PhD or MSc in Data Science, Physics, Mathematics, Computer Science, or a related field.
• 10+ years of experience in data science, with a focus on client behavior analytics.
• Strong hands-on experience with recommender systems (collaborative filtering, content-based filtering, hybrid models), machine learning, deep learning, and statistical modeling.
• Proficiency in Python (Pandas, NumPy, Scikit-learn, TensorFlow/PyTorch) and SQL.
• Experience with NLP/AI tools for customer interaction analysis and proven leadership, team coaching, and management skills.
• Fluency in English.

Culture & Benefits

• Attractive remuneration package.
• Private health insurance and corporate pension fund.
• Intellectually stimulating work environment.
• Continuous personal development and international training opportunities.

Hiring process

• Artificial intelligence (AI) tools may support parts of the hiring process, such as reviewing applications or assessing responses, but final hiring decisions are made by humans.