Biostatistician & Data Science Specialist

About the role

Reneco Wildlife Consultancy is seeking a Biostatistician & Data Science Specialist to support conservation, environmental monitoring and applied research initiatives in Abu Dhabi. The role combines advanced analytics, machine learning and AI to turn large ecological datasets into actionable insights.

Key responsibilities

• Deliver statistical analyses, data interpretation and reporting to support evidence‑based decision‑making across conservation and research projects.
• Clean, structure, integrate and manage large, complex datasets while developing reliable data pipelines.
• Design, develop and implement AI and machine‑learning models to address operational and scientific challenges.
• Develop and deploy AI‑driven applications such as automated monitoring systems, sensor integration, dashboards, APIs and intelligent decision‑support tools.
• Collaborate with multidisciplinary teams, researchers and international partners to bridge scientific research with practical applications.
• Generate actionable insights by identifying patterns, trends and anomalies within environmental, biological and operational datasets.

Required profile

• PhD in Data Science, Artificial Intelligence, Machine Learning, Computer Science or a related field.
• 2–5 years of experience in Data Science, Machine Learning or Artificial Intelligence (academic or industry).
• Proven experience developing and implementing AI/ML models on real‑world datasets, preferably with environmental or conservation data.
• Fluent English; French and/or Arabic are a strong advantage.

Required skills

• Strong proficiency in Python and/or R for statistical analysis, machine learning and data visualization.
• Strong proficiency in SQL and database management.
• Solid understanding of machine‑learning methodologies, model evaluation and validation techniques.
• Expertise in data preprocessing, feature engineering and analytical pipeline development.
• Familiarity with modern AI applications including large language models, AI agents, computer vision and geospatial analytics.
• Knowledge of cloud computing environments, MLOps practices, Docker and model deployment frameworks (advantage).