5,281 Senior Research Positions jobs in Kenya

• Nairobi Kenya
• Posted 1 hour ago
• Deadline: 09 October 2025
• Partner: CIFOR-ICRAF

CIFOR-ICRAF
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Under the supervision of the head of SPACIAL the Spatial Data Scientist – Remote Sensing will lead and implement advanced remote sensing analysis tasks, including processing of optical and SAR data, timeseries analysis, and predictive modeling with primary focus on the modeling of temporal dynamics across complex landscapes. The position will support a range of projects and programmes across CIFOR-ICRAF, including Regreening Africa, Knowledge for Great Green Wall Action (K4GGWA). Towards Ending Drought Emergencies (Twende), and upcoming assessments of soil and land health with funding from NORAD.

Duties and responsibilities

Spatial data science

• Optical data processing and analysis, including from sensors such as Sentinel 2 and Landsat 8/9.
• SAR data processing and analysis, primarily Sentinel 1.
• Timeseries analysis, including detection of trends and anomalies in temporal data (vegetation, precipitation, land surface temperatures, etc)
• Predictive modeling of time series data, including forecasting where relevant.
• Applications of machine learning for predictive modeling and mapping of indicators relevant to assessment of ecosystem health using a combination of field data and remote sensing.
• Spatial data analysis tasks, including spatial queries, vector data extraction, processing, and cleaning.
• General data analysis and report writing.
• Supervise a team of junior spatial data scientists and developers.
• Develop communication products/outputs where relevant.

Capacity development

• Lead internal capacity development seminars within CIFOR-ICRAF.
• Capacity development of partners and stakeholders through workshops as part of projects with particular emphasis on spatial data processing and modeling.

Stakeholder engagement

• Work closely with the CIFOR-ICRAF stakeholder engagement team (SHARED) to provide analytical outputs that feed into project delivery, for example monitoring outputs as part of the Great Green Wall.
• Contribute to stakeholder engagement events as part of the development of decision support tools and platforms.

Various Other Tasks

• Contribute to micro-dashboard development as part of the Global Resilience Impact Tracker platform
• Support projects and programs with analytical support and stakeholder engagement with decision makers.
• Lead and/or contribute to scientific papers.
• Contribute to proposal development and writing.

Requirements
Education, knowledge and experience

• MSc degree in remote sensing and spatial data science is required with proven ability to conduct highly complex analytical tasks.
• Excellent interpersonal skills.
• Excellent written and spoken English.
• Advanced computer programming skills in R Statistics, some knowledge of Python and/or Julia, database technologies, and data management.

Personal Attributes And Competencies

• Excellent skills in organizing and priority setting, with the ability to work effectively under time pressure and manage multiple priorities.
• Have initiative and capable of working independently as well as an effective team player.
• Good interpersonal and communication skills, with the ability to effectively interact with people in a multi-disciplinary and multi-cultural environment.
• Experience working with a wide and diverse network of groups and individuals.
• Proactive, target driven, and diligent.
• Works with trustworthiness and integrity.

Education, knowledge and experience

• MSc degree in remote sensing and spatial data science is required with proven ability to conduct highly complex analytical tasks.
• Advanced computer programming skills in R Statistics, some knowledge of Python and/or Julia, database technologies, and data management.

Terms and conditions

• This is a Globally Recruited Staff (GRS) position. CIFOR-ICRAF offers competitive remuneration in USD, commensurate with skills and experience.
• The appointment will be for two (2) year period, inclusive of a six-month probationary period, with the possibility of extension contingent upon performance, continued relevance of the position and available resources.
• The duty station will be in Kenya, Nairobi.

Learn more

• Lead and manage multiple scientific research projects in environmental science.
• Develop strategic research plans and roadmaps.
• Supervise and mentor a team of remote research scientists and technicians.
• Oversee experimental design, data collection, and analysis.
• Write and submit grant proposals to secure research funding.
• Foster collaborations with external research institutions and industry partners.
• Ensure scientific integrity and adherence to research ethics.
• Disseminate research findings through publications, presentations, and reports.
• Manage research budgets and resources effectively.
• Stay abreast of advancements in environmental science and research methodologies.

• Ph.D. in Environmental Science, Ecology, Climate Science, or a related field.
• Minimum of 8 years of research experience, with at least 3 years in a leadership or management role.
• Proven track record in securing research grants and managing large-scale research projects.
• Expertise in scientific research methodologies, data analysis, and interpretation.
• Strong leadership, team-building, and interpersonal skills.
• Excellent written and verbal communication skills, including grant writing and presentation experience.
• Proficiency in scientific software and data analysis tools.
• Demonstrated ability to work independently and manage diverse research portfolios remotely.
• Experience in publishing research in high-impact journals.
• A passion for environmental sustainability and scientific innovation.

• Lead the design and implementation of sophisticated statistical models and machine learning algorithms for scientific data analysis.
• Develop and manage data pipelines for ingesting, cleaning, transforming, and analyzing large-scale scientific datasets from various sources (e.g., experimental, observational, genomic).
• Collaborate closely with domain experts (biologists, chemists, physicists, etc.) to understand research questions and translate them into data science problems.
• Mentor and guide a team of data scientists, providing technical leadership and fostering professional development.
• Design and conduct rigorous A/B testing and validation studies to assess the performance of models and hypotheses.
• Develop reproducible research workflows and ensure best practices in coding, version control, and documentation.
• Communicate complex analytical findings and insights effectively to both technical and non-technical audiences through clear visualizations and presentations.
• Identify opportunities to leverage new data science techniques and technologies to solve challenging scientific problems.
• Contribute to grant proposals and publications by providing data analysis expertise and insights.
• Ensure data privacy, security, and ethical considerations are maintained throughout all data science projects.
• Stay current with the latest advancements in data science, machine learning, artificial intelligence, and their applications in scientific research.

• Ph.D. or Master's degree in Data Science, Computer Science, Statistics, Mathematics, Physics, or a related quantitative field.
• A minimum of 7 years of progressive experience in data science, with a significant portion focused on scientific or research applications.
• Demonstrated experience in leading data science projects and mentoring junior team members.
• Expertise in programming languages such as Python or R, and proficiency with relevant data science libraries (e.g., scikit-learn, TensorFlow, PyTorch, Pandas, NumPy).
• Strong understanding of statistical modeling, machine learning algorithms, and experimental design.
• Experience with big data technologies (e.g., Spark, Hadoop) and cloud platforms (AWS, Azure, GCP) is highly desirable.
• Excellent data visualization skills and experience with tools like Matplotlib, Seaborn, or Tableau.
• Exceptional analytical, problem-solving, and critical thinking abilities.
• Superb communication and collaboration skills, with the ability to work effectively in a distributed, remote team.
• Experience with bioinformatics, cheminformatics, or other specialized scientific data analysis is a plus.

• Lead the design and implementation of complex data science projects to address critical research questions.
• Develop and apply advanced statistical methods, machine learning algorithms, and predictive models to large, complex scientific datasets.
• Extract, clean, transform, and analyze diverse data sources (e.g., experimental data, simulations, observational data).
• Visualize complex data and communicate findings clearly and effectively to researchers, stakeholders, and collaborators.
• Mentor and guide junior data scientists and research staff in data analysis methodologies.
• Collaborate with principal investigators and research teams to define research objectives and data requirements.
• Stay abreast of the latest advancements in data science, machine learning, artificial intelligence, and their applications in scientific research.
• Develop and maintain robust data pipelines and computational workflows.
• Evaluate and implement new tools and technologies for data analysis and modeling.
• Contribute to grant proposals and research publications by providing data science expertise.
• Ensure the reproducibility and validity of analytical results.
• Identify opportunities to leverage data for novel discoveries and advancements.
• Manage data governance, privacy, and ethical considerations in research data analysis.
• Present research findings at scientific conferences and workshops.
• Troubleshoot and resolve complex analytical challenges.

• Ph.D. in Data Science, Statistics, Computer Science, Physics, Mathematics, or a related quantitative field.
• Minimum of 10 years of experience as a Data Scientist, with a significant focus on scientific research applications.
• Extensive expertise in statistical modeling, machine learning techniques (e.g., deep learning, Bayesian methods, reinforcement learning), and experimental design.
• Proficiency in programming languages such as Python or R, and experience with relevant libraries (e.g., TensorFlow, PyTorch, scikit-learn).
• Strong experience with big data technologies and distributed computing frameworks (e.g., Spark, Hadoop).
• Excellent data visualization skills and experience with tools like Matplotlib, Seaborn, or Tableau.
• Demonstrated ability to lead complex analytical projects and mentor junior team members.
• Exceptional problem-solving, critical-thinking, and analytical skills.
• Outstanding communication and presentation skills, capable of explaining complex technical concepts to both technical and non-technical audiences remotely.
• Ability to work independently, manage priorities, and drive projects to completion in a remote setting.
• Experience in a specific scientific domain (e.g., genomics, astrophysics, bioinformatics, computational chemistry) is highly desirable.
• Strong understanding of data management best practices and database technologies.