Position: Energy Advisor (Data Scientist)

Organization: Deutsche Gesellschaft für Internationale Zusammenarbeit (GIZ) GmbH

Location: Delhi

Responsibilities

• In close collaboration with the implementing partners of the project-SunSeed APV and Kanoda- the advisor shall manage and execute the research and data analysis tasks and objectives for the DeveloPPP project entitled “Economic and environmental benefits through Agrivoltaic systems in India”.
• The advisor will be responsible for designing and conducting experiments to generate research materials, technical reports and scientifically-sound interpretations and recommendations for crops grown in an Agriphotovoltaics environment.
• S/He will serve as the project manager for defining solar generation & crop growth data collection and will use statistical methods and software programming to conduct data analysis.
• The data and research will be used to help create solar generation forecasting tools, light & microclimate simulation models, and crop yield models to address scientific challenges in designing Agriphotovoltaic projects.
• The advisor will leverage data science to analyse complex data, develop and test features to help develop environmental and agronomic models.

Core Scope of Tasks

• Serve as the research and data analysis expert for the project. Manage and execute all research activities and data analysis and interpretation.
• Plan Design of Experiments (DoE), establish, manage, and report scientific trials based on developed protocols and maintenance of records of procedures.
• Creation of a framework to analyze and post-process data for quantifying crop growth, irrigation requirements, and solar generation under competing light conditions in an Agriphotovoltaics environment. Multiple Agriphotovoltaics installations would serve as the source of data.
• Manage aspects related to sampling, data accuracy, storage, post processing, pattern recognition using data visualization software or otherwise, for all instrumentation.
• Organize data, conduct preliminary statistical analyses, and summarize results for inclusion in reports, presentations, or publications.
• Coordinate use and maintenance of research equipment, sensors, data collection tools and hardware. Maintain and troubleshoot meteorological, soil and plant data measurement instrumentation.
• Work with other project collaborators –mainly plant biophysicists, agronomists, data collection engineers and programmers – to decide on aspects related to data sampling, error flagging, pattern recognition, future forecasting amongst other things.
• Project manage the development of the simulation models involving a team of APV experts and software developers.
• Write scientific white papers and articles about the project research for publication.
• Keep informed about new technologies and techniques in area of responsibility.
• Manage, supervise, and mentor other employees within the functional group.
• Frequent travel to field sites, implementing instructions, and communicating with team members to ensure proper collection of all required data.

Other duties/additional tasks

The below is a list of sample data that would be collected at the site:

• Light field inside the APV zone, where each measurement would have space, time, and intensity attributes, measured manually.
• PAR measurement at specific spatial coordinates using pyranometers, with data extraction at set intervals.
• Photosynthesis rates and photosynthesis response curves wrt to temperature, light, CO2, and water.
• Leaf Area Index measurement using LAI meters.
• Optical properties of various materials like solar panels, shade nets, mulches, plant leaves and soil.
• Temperature field measurement of various surfaces including solar panels, soil and crop leaves with space and time attributes using sensors.
• Photogrammetry data of sample plants to be classified and filed as per time, and space coordinates.
• Meteorological data like radiation, wind velocity, air temperature, and relative humidity.
• Soil moisture data.

E.               Required Qualifications, Experience and Competencies

• Education/training: University qualification in Engineering, Statistics, data science, agronomy, crop biophysics, photovoltaics, APV, agricultural economics or similar fields.
• PhD with one year of professional experience, master’s with two years of professional experience, or bachelor’s with at least four years of relevant experience is preferred.
• Knowledge of agriculture systems modelling and simulation including crop and water simulation models and software.
• Demonstrated experience building machine learning, simulation, and/or statistical models with ability to apply data science to real-world problems.
• Python coding skills for data analysis and modelling, including experience with standard data science packages.
• Good understanding of the workings of scientific and electronic equipment, sensors, and field data collection equipment (i.e., weather stations, temperature sensors, albedometers etc.).
• Ability to work independently on maintaining, troubleshooting, and fixing field equipment in agricultural settings.
• Language: Excellent language skills in English and Hindi.
• Affinity for field work.
• Initiative, proactive and working under minimum supervision.
• Excellent communication, facilitation, and presentation skills with ability to interact effectively with people from a mainly rural background.