Biostatistician & Data Science Specialist
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Key skills for this role
About the Role
Reneco International Wildlife Consultants seeks a Biostatistician/Data Scientist to apply advanced analytics, machine learning, and AI to wildlife conservation. The role involves managing large datasets, developing AI models, and collaborating with multidisciplinary teams.
Key Skills for This Role
Responsibilities
- Deliver statistical analyses, data interpretation, and reporting to support evidence based decision making
- 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 and operational solutions, including automated monitoring systems, dashboards, APIs, and decision support tools
- Collaborate with multidisciplinary teams, researchers, and international partners
- Generate actionable insights by identifying patterns, trends, and anomalies within environmental, biological, and operational datasets
- Support the adoption of innovative data science and artificial intelligence approaches across conservation initiatives
- Contribute to capacity building, knowledge transfer, and team coordination
- Communicate scientific findings through peer reviewed articles and conferences, and supervise students
Requirements
- PhD in Data Science, Artificial Intelligence, Machine Learning, Computer Science, or a related field
- 2–5 years of experience in Data Science, Machine Learning, and/or Artificial Intelligence (academic or industry)
- Proven experience developing and implementing AI/ML models on real world datasets
- 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
- Ability to analyse, clean, and manage large and complex datasets
- Fluent English is required
- French and/or Arabic would be a strong advantage
Full Job Posting
About Reneco
- Reneco implements global conservation strategy to restore and preserve Houbara bustard populations.
- The organization generates and manages large datasets spanning ecology, demography, reproductive physiology, behaviour, veterinary science, conservation genomics, climate, and environmental monitoring.
Key Responsibilities
- Deliver statistical analyses, data interpretation, and reporting to support evidence based decision making.
- 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 and operational solutions, including automated monitoring systems, sensor integration, dashboards, APIs, automated reporting, and intelligent decision support tools.
- Collaborate with multidisciplinary teams, researchers, and international partners to bridge scientific research with practical applications.
- Ensure effective follow up and implementation of collaborative projects with universities and research institutions.
- Generate actionable insights by identifying patterns, trends, and anomalies within environmental, biological, and operational datasets.
- Support the adoption of innovative data science and artificial intelligence approaches across conservation and environmental intelligence initiatives.
- Contribute to capacity building, knowledge transfer, and team coordination and management.
- Communication of scientific findings (peer review article, conferences) and supervision of students.
Education
- PhD in Data Science, Artificial Intelligence, Machine Learning, Computer Science, or a related field.
Professional Experience & Skills
- 2–5 years of experience in Data Science, Machine Learning, and/or Artificial Intelligence (academic or industry).
- Proven experience developing and implementing AI/ML models on real world datasets.
- Exposure to environmental, biological, ecological, or conservation related datasets would be highly beneficial.
- 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.
- Ability to analyse, clean, and manage large and complex datasets.
- Expertise in data preprocessing, feature engineering, and analytical pipeline development.
- Familiarity with modern AI applications, including LLMs, AI agents, computer vision, and geospatial analytics.
- Knowledge of cloud computing environments, MLOps practices, Docker, and model deployment frameworks is an advantage.
- Strong analytical, problem solving, and communication skills.
- Fluent English is required. French and/or Arabic would be a strong advantage.
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