Crop Forecasting & Data Analyst

About the role

This role combines weekly crop forecasting with data management and analysis for a tea estate. Forecasting is the main responsibility during the data remediation project, which also involves transcription and validation of historical records; after handover the focus moves to forecasting, keeping the database current and running analysis. The analyst must be based on an estate and spend time in the field and in estate record rooms.

Key responsibilities

• Crop forecasting: weekly green leaf forecasts by estate and field, and rolling monthly forecasts, with hand-picked and mechanically harvested leaf forecasted separately
• Improve the shoot-count method and build and maintain forecasting models combining shoot counts with rainfall, plucking round length, pruning cycle, section age, infill plantings, fertiliser timing, cultivar and seasonality
• Forecast outgrower leaf volumes with the Outgrower Manager and track forecast accuracy weekly and monthly against a 5% variance standard
• Data management: enter and validate historical records from field books, spreadsheets, lab reports and soil maps into a central database covering block registry, soil maps, soil and leaf analysis, rain gauges, inputs, pruning, harvesting and yield, linked to block IDs
• Validate, de-duplicate and check batches against a 10% stratified sample, then train estate clerks and supervisors to capture current data on weekly and monthly cycles
• Maintain a data dictionary and the block registry, record infill plantings, and handle estate trial data separately from production data
• Dashboards and reporting: maintain a live dashboard, produce weekly and monthly management reports, flag yield or quality falls, and answer ad hoc analysis requests
• Analyse trial results with trial owners using methods such as analysis of variance, and assess the effect of infill plantings on yield and forecast accuracy

Required profile

• Bachelor's degree in a quantitative field (Statistics, Actuarial Science, Data Science, Applied Mathematics, Economics, Computer Science or similar)
• At least 3 years' experience in forecasting, data analysis or data management
• Experience building forecasts or predictive models from real operational data and measuring their accuracy
• Proven accuracy and patience in detailed data entry, cleaning and checking, including from handwritten or scanned records
• Willingness to work on an estate and spend time in the field and record rooms
• Desirable: Master's degree, experience on a digitisation or data migration project, and experience in agriculture, agribusiness, commodities, supply chain or manufacturing planning

Required skills

• Working knowledge of SQL and relational databases, and advanced Excel
• Experience building dashboards or reports; Power BI, Tableau, Superset or Metabase is helpful
• Desirable: PostgreSQL, GIS or mapping tools such as PostGIS, time series methods, sampling design, experimental design and statistical analysis of field trials
• Knowledge of tea or other perennial crops such as coffee, sugar or avocado