Consultant – Middle East Crisis Analysis Data Scientist and Front End Developer – Remote At Mercy Corps

Background:

Mercy Corps is a leading global organization powered by the belief that a better world is possible. In disaster, in hardship, in more than 40 countries around the world, we partner to put bold solutions into action — helping people triumph over adversity and build stronger communities from within.

Over the past eight years, Mercy Corps has established a reputation for quality and timely data and analysis through its network of Crisis Analysis teams. Through Crisis Analysis, the agency has carved out a niche among information providers in the humanitarian and development space, owing to the granularity, reactivity and holistic approach of our products, which focus on some of the most hard-to-reach, data-poor and complex contexts requiring assistance. This is underpinned by Mercy Corps’ status as an operational INGO, which ensures that analysis products are practicable and relevant for humanitarian actors.

Purpose / Project Description:

The Middle East Regional Data Analysis Hub (MERDAH) is a platform where quantitative indicators developed by ME Crisis Analysis teams can be accessed, analyzed, and downloaded. The dashboard aims to show MC’s capacity to develop timely and relevant quantitative analysis in the ME region and for other peers and external stakeholders to use, and to eventually serve several key objectives/purposes as part of our evidence-driven commitment. Dashboard modules are regionally cross-cutting by theme or approach; for example, agriculture analysis (theme) or price predictions (approach). The MERDAH currently covers Syria, Iraq, Palestine, Lebanon, and Yemen. The MERDAH will also host the drought and flooding anticipatory action modules produced for the ECHO-funded MEACAM project.

The platform allows users to freely download quantitative indicators useful for targeting (Operational actors; Peer agencies)to identify the most vulnerable locations for interventionsand advocacy & influence (donors; local/national Governments; media), which are not immediately operational but useful for understanding the context to improve decision-making. For example, Mercy Corps LCAT developed an economic vulnerability indicator using night lights satellite imagery the Lebanon country team used to target cadasters for a MPCA program. The CA-SYR team used satellite imagery to measure the effect of the second-consecutive drought in northeast Syria to highlight the scale and intensity of the repercussions on farmers, the results of which were featured in a NES Forum publication advocating for funding to alleviate the situation.

The continual enhancement of the MERDAH is necessary to obtain and maintain a high level of relevance and utility to the community, and serve as an attraction to donors. Further, timely additions to the MERDAH ensures that Mercy Corps is the “first to market” to deliver actionable spatial and quantitative analysis to the humanitarian community.

Consultant Objective:

A front-end developer, in collaboration with technical support and close coordination with the Regional Data Analysis Specialist and the CA-SYR Director, Yemen CA Team Lead, and Lebanon CA Team Lead will need to produce the following for the MERDAH:

Syria – 22.5 days

Yemen – 23.5 days

Lebanon – 13.5 days

MEACAM – 42 days

Total – 101.5

Syria

1. SMEB/MEB with input cash gap (2 days)
   1. Add the historic and predicted price of the SMEB and MEB.
   2. Add a user-entered monthly transfer value to calculate the “cash gap” between the hypothetical transfer value and (S)MEB price.
2. “Make a basket” feature (2.5 days)
   1. Add a “make a basket” feature that allows users to select each available WFP item and define a quantity for each item.
   2. Add a line graph displaying the sum of all the selected item prices, multiplied by the selected quantity. This line graph will show the historic and predicted prices.
      1. Predicted basket prices are simply the sum of the existing predicted (selected) item prices.
3. Pass-through effect (4 days)
   1. Develop a module that measures the pass-through effect of all WFP items, including wage rates.
      1. SYP/USD, TRY/SYP, and TRY/USD on item prices.
   2. Allow the user to select the date range to calculate the pass-through effect.
      1. Minimum 10 months.
      2. Allow up to three ranges to compare changes in the pass-through effect over time.
   3. Display the pass-through effects in a bar chart and mark their statistical significance.
      1. Side-by-side bar chart for multiple time periods.
4. Add NLR time trends to subdistrict GDP estimate map (4 days)
   1. Make a line graph of monthly night lights reflectance (NLR) for subdistricts selected on the regional GDP map.
      1. If no subdistricts are selected, then the NLR for the whole of Syria will be displayed.
      2. Ability to select up to 5 different subdistricts, which creates 5 lines on the line chart.
   2. NLR images piped in from Google Earth Engine.
5. Agriculture Module (10 days)
   1. Measure the NDVI and NDMI of agricultural areas in Syria using Sentinel-2 data.
   2. Calculate NDVI and NDMI in agricultural areas near canals, rivers, and in-land.
      1. Visualize changes in these indicators in a line graph akin to Figure 4 in a 2022 CA-Syria report.
      2. Map these changes on an interactive map akin to Figures 7 to 9 in a 2022 CA-Syria report.
   3. Relate changes in NDVI/NDMI to agriculture indicators recorded in REACH’s HSOS assessment.
      1. Community-level NDVI/NDMI changes to community-level REACH indicators.

Yemen

1. SMEB/MEB with input cash gap (2 days)
   1. Add the historic and predicted price of the SMEB and MEB.
   2. Add a user-entered monthly transfer value to calculate the “cash gap” between the hypothetical transfer value and (S)MEB price.
2. “Make a basket” feature (2.5 days)
   1. Add a “make a basket” feature that allows users to select each available WFP item and define a quantity for each item.
   2. Add a line graph displaying the sum of all the selected item prices, multiplied by the selected quantity. This line graph will show the historic and predicted prices.
   3. Predicted basket prices are simply the sum of the existing predicted (selected) item prices.
3. Pass-through effect (4 days)
   1. Develop a module that measures the pass-through effect of all WFP items, including wage rates.
      1. YER/USD on item prices.
   2. Allow the user to select the date range to calculate the pass-through effect.
      1. Minimum 10 months.
      2. Allow up to three ranges to compare changes in the pass-through effect over time.
   3. Display the pass-through effects in a bar chart and mark their statistical significance.
      1. Side-by-side bar chart for multiple time periods.
4. Price forecasting: Part 1 (9 days)
   1. Add item and MEB projections using REACH Market Monitoring price data (JMMI)
   2. Develop USD projections for items and MEB.
   3. Add graph that shows past MERDAH MEB predictions compared to observed WFP/REACH MEB prices
      1. Starting from September 2022.
   4. Develop MEB affordability predictions for the WFP MEB price.
      1. Because WFP records wage rates.
   5. Develop individual market forecasts for the MEB.
      1. REACH and WFP prices.
5. Price forecasting: Part 2 (6 days)
   1. Develop item forecasts for individual markets.
   2. Develop a now-casting model to predict prices in markets with incomplete data.

Lebanon

1. Migrate LCAT dashboard to MERDAH (3 days)
   1. Replace the Lebanon module in the MERDAH with the LCAT dashboard.
      1. Ensure they are synced, so changes in the LCAT dashboard are reflected in the Lebanon MERDAH version simultaneously.
   2. In the Economic Vulnerability Index module:
      1. Change the default to “population-weighted”
      2. Add a filtering option to select the top 10 most vulnerable cadasters in a district, ranked by the EVS score. This would change depending on whether the user selected population weighted or not. Then allow users to export this top-10 selection to a CSV.
2. “Make a basket” feature (2.5 days)
   1. Add a “make a basket” feature that allows users to select each available WFP item and define a quantity for each item.
   2. Add a line graph displaying the sum of all the selected item prices, multiplied by the selected quantity. This line graph will show the historic and predicted prices.
   3. Predicted basket prices are simply the sum of the existing predicted (selected) item prices.
3. Electricity consumption/tensions monitoring dashboard (8 days)
   1. Build a dashboard around the research on the connection between social perceptions and night lights.

MEACAM

1. Change over the MERDAH to a Shiny app (5 days)
   1. Migrate the MERDAH app to a Shiny app.
   2. Change the affordability graphs so that the x-axis is each zone of control and the bar fill is the date for the past 6 months.
   3. Change the line graph color palette for governorates in Syria and Lebanon to more distinct colors because the current colors are too similar.
   4. Change the Syria regional GDP estimate map to a choropleth.
   5. Repair the functionality of the governorate and subdistrict selection for the regional GDP estimate graph.
   6. Change GDP estimate map selection from district to subdistrict.
   7. Change the CSV export to the selection on the module, as opposed to the entire dataset.
   8. Add percentage change (base year/latest year) feature to GDP estimate tab, which will update the map with percentage change instead of GDP estimate levels.
2. Google cloud credits
   1. Purchase $1,000 USD of Google Cloud Credits to support Google Earth Engine pipelines.
3. Shiny performance upgrade
   1. Purchase one year of the “Basic” R Shiny Apps for the MERDAH ($550).
4. Build weather data pipelines (5 days)
   1. Identify and create pipelines for granular (<5km) precipitation and temperature data.
      1. Data can be satellite derived, such as CHIRPS and MODIS.
   2. Identify and create pipelines for granular weather forecast data.
   3. Create pipelines for appropriate existing APIs featuring geospatial drought and flooding data.
5. Create functional drought module (10 days)
   1. Create the outline of the module with a map that shows areas susceptible to drought, given weather forecasts (precipitation levels & temperature).
   2. Work with MC to establish the resultant analysis from the module.
      1. Build the first build of the module assuming that weather/impact forecasts are functional. Focus on displaying the output of the affected population, severity, etc…
      2. Add graphs of the number of people affected and the projected amount of additional food, water, and livelihood insecurity.
   3. Start with Syria and replicate for Iraq and Yemen.
6. Create skeleton module for flood module (10 days)
   1. Create the outline of a module with a map that shows areas susceptible to flooding, given weather forecasts (precipitation levels) and historical flood risk.
   2. Work with MC to establish the resultant analysis from the module.
      1. Build the first build of the module assuming that weather/impact forecasts are functional. Focus on displaying the output of the affected population, severity, etc…
   3. Create for Syria, Iraq, and Yemen
7. Work with MC to develop a statistical model (5 days)
   1. Work with Mercy Corps to develop statistical models predicting the humanitarian impact of drought and flooding.
8. Operationalize national-level flood extent methodology (7 days)
   1. Add historic flood extents by year to the flood module.
      1. Flood extents collected from 3rd party data and created from Sentinel-1 satellite imagery analysis.
   2. Flood extents are calculated every month, so the yearly extents are continuously updated with newly available satellite imagery.

Consultant Activities:

• Based on consultations with relevant team members, identify relevant data to display and design an intuitive and simple user interface for the dashboard.
• Develop the interactive geospatial dashboard.
• Present the dashboard to key internal Mercy Corps stakeholders and adjust as appropriate.
• Deliver the dashboard with instructions on editing and maintaining going forward.

Required Experience & Skills:

• 7+ years of experience in relevant roles developing front-end geospatial dashboards.
• Demonstrated expertise in designing and developing innovative GIS / interactive mapping solutions based on understanding of diverse stakeholder requirements.
• Experience designing intuitive, user-friendly interfaces to display and support analysis of complex information.
• Strong briefing, communication and presentation skills.
• Experience within humanitarian, development or conflict analysis settings and knowledge of the humanitarian sector preferred.

Timeframe / Schedule:

Work to be completed within a six months

The Consultant will report to:

Regional Quantitative Analyst

Consultant will work closely with:

Regional Crisis Analysis Advisor. Mercy Corps’ Iraq, Syria and Yemen teams.

Diversity, Equity & Inclusion
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