Data Analyst

Mohammed VI Polytechnic University is an institution dedicated to research and innovation in Africa and aims to position itself among world-renowned universities in its fields

The University is engaged in economic and human development and puts research and innovation at the forefront of African development. A mechanism that enables it to consolidate Morocco's frontline position in these fields, in a unique partnership-based approach and boosting skills training relevant for the future of Africa.

Located in the municipality of Benguerir, in the very heart of the Green City, Mohammed VI Polytechnic University aspires to leave its mark nationally, continentally, and globally.

These Data Analyst roles are central to the success of the project "Developing a Data-Driven Platform for Personalized Fertilizer Recommendations to Optimize Crop Productivity and Sustainability". The analysts will take the lead in collecting, managing, and structuring complex agricultural datasets—particularly soil, environmental, and crop data. Their work will directly feed into the machine learning and optimization models used to deliver customized fertilizer recommendations.

The research engineers will work closely with faculty, developers, and analysts across the following key domains:

1. Strategic Data Acquisition & Integration

• Identify relevant data sources within UM6P, OCP, external partners, and open platforms.
• Acquire, verify, and compile datasets covering soil properties, fertilizer inputs, climate data, crop performance, and geolocation.
• Coordinate with institutions and research programs to access historical and in-progress field trial data.

2. Data Management & Infrastructure

• Develop and maintain a centralized data repository with proper versioning and metadata tracking.
• Standardize heterogeneous data formats for integration into analytical and modeling pipelines.
• Ensure data quality through validation rules, consistency checks, and documentation of gaps.

3. Data Curation & Enrichment

• Apply advanced data cleaning, transformation, and enrichment techniques to prepare high-quality, analysis-ready datasets.
• Structure time-series, spatial, and categorical data to support downstream modeling and simulation work.
• Annotate datasets with key agronomic and geospatial features to improve model interpretability.

4. Analytical Support & Reporting

• Conduct exploratory and descriptive statistical analysis to extract insights and trends from large datasets.
• Create detailed data summaries and reports to support decision-making by research engineers and principal investigators.
• Design visualizations and dashboards to communicate findings clearly to both technical and non-technical audiences.

5. Documentation & Collaboration

• Maintain detailed logs of data lineage, processing pipelines, and decisions related to data handling.
• Collaborate with model developers to align data features with modeling objectives.
• Contribute to scientific documentation, deliverables, and publications with well-supported data summaries and visual materials.

Required Qualifications:

• Master's degree or equivalent Data Science, Applied Statistics, Information Systems or related fields.
• Demonstrated experience in handling large, diverse, and complex datasets.
• Advanced proficiency in Python (pandas, NumPy, matplotlib), R, or other data analytics tools.
• Strong understanding of database design and data structuring for modeling use cases.
• Excellent skills in data cleaning, merging, transformation, and validation.

Application Process:

Applicants should submit the following documents:

1. Cover letter outlining relevant experience and motivation.
2. Curriculum Vitae (CV)
3. Contact details of two references.

Applications will be reviewed on a rolling basis until the position is filled.

For inquiries, please contact

UM6P.