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Tenders are invited for Consultancy in Data Science, Predictive Modelling, Remote Sensing, Time Series and Methodological Support for Early Warning Systems. Closing Date: 30 Sep 2026 Type: Consultancy Action Against Hunger in Senegal is looking to recrute the profesional services for a Consultancy for advanced analysis, development of experimental predictive models, analysis of historical time series and support for the definition of alert thresholds for the Pastoral Early Warning System. Project name: Strategic alliances for anticipatory action in response to food and pastoral crises in the Sahel. Action Against Hunger aims to hire an external consultant to strengthen the analytical capacities of PEWS through the exploration, development and documentation of advanced analysis methods, predictive or nowcasting models, historical time-series analysis and the proposal of technical thresholds, taking into account relevant temporal and seasonal dynamics, in order to support early warning, anticipatory action and humanitarian decision-making. The consultancy will cover the advanced analytical components of PEWS. It will include the analysis of historical data, the exploration of predictive or nowcasting models, support for the definition of technical thresholds, analysis of the relevance of selected target variables and the production of methodological recommendations for gradual integration into PEWS information products. The consultancy will cover the advanced analytical components of PEWS. It will include the analysis of historical data, the exploration of predictive or nowcasting models, support for the definition of technical thresholds, analysis of the relevance of selected target variables and the production of methodological recommendations for gradual integration into PEWS information products. It will include, in particular: Review of available data sources for predictive analysis or nowcasting, primarily based on datasets and sources provided by ACF and SensingTools and complemented, where relevant, by targeted additional sources identified by the consulting firm; Analysis of data quality, gaps, biases, breaks in series, update frequency and spatial and temporal comparability; Analysis of temporal and seasonal characteristics of the available data, including differences in update frequency, seasonal cycles, lagged relationships between predictors and outcomes, cumulative effects, critical pastoral periods and the suitability of different forecast horizons for anticipatory action; Preparation of reproducible analytical datasets, accompanied by a data dictionary and documentation of the processing performed; Experimental development of statistical, machine-learning, forecasting or nowcasting models, depending on data availability and objectives validated with ACF and SensingTools, including the assessment of alternative temporal structures and forecast horizons where relevant; Consideration of SensingTools methodological contributions on data, models, social sensors, natural language processing and perception analysis; Analysis of normalized historical time series, for example through anomalies, z-scores, percentiles or other explainable methods, to support discussions on technical thresholds; Formulation of recommendations on thresholds, warning signals or interpretation rules that can be tested, validated or calibrated with technical teams, institutional partners or communities. This consultancy is expected to be carried out remotely. How to apply The consultancy shall be carried out by a consulting firm, consulting team, applied research centre or technical entity with proven experience in the following areas: Data science, applied statistics, machine learning or predictive modelling; Time-series analysis, forecasting, nowcasting or near-real-time estimation methods, including the treatment of seasonality, temporal lags and time-aware model validation; Geospatial analysis, remote sensing, agroclimatic and environmental indicators; Food security, pastoral livelihoods and agro-pastoral seasonal dynamics, early warning, anticipatory action or humanitarian risk analysis; Preparation of analytical datasets, technical documentation and reproducibility of processing; Responsible use of artificial intelligence, model explainability and data protection in humanitarian contexts; Capacity to coordinate with technical partners such as SensingTools, particularly on data, models, social sensors or perception analyses; Technical training, capacity transfer and production of operational documentation. Interested entities shall submit: A duly completed application form provided by ACF, including relevant information on the consulting firm or entity, as well as on the experts and key members of the proposed consulting team; A technical proposal describing their understanding of the mandate, proposed methodology, models or families of methods envisaged, validation strategy and anticipated limitations; A financial proposal detailed by activity, profile, number of days, deliverables, possible licenses and recurring costs; CVs, including copies of diplomas, of the members of the proposed technical team involved in the direct implementation and supervision of the consultancy services provided; Examples of similar experience, reports, models, repositories, publications or products; A note on data management, reproducibility, model explainability and data protection; Legal and tax documentation required for contracting. For further information and how to apply, please download the Terms of Reference. Offers must be submitted by email to eufernandez@accioncontraelhambre.org before: September 30th, 2026. Tender Link : https://reliefweb.int/job/4230061/consultancy-data-science-predictive-modelling-remote-sensing-time-series-and-methodological-support-early-warning-systems
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