Senior Data Scientist, Human Centered Weather Forecasts- Development Innovation Lab

About The Development Innovation Lab:

at the uses the tools of economics to develop innovations with the potential to benefit millions of people in low- and middle-income countries. It was founded and is led by Nobel laureate Michael Kremer.

Human-Centered Weather Forecast Initiative:

Initiative works with governments, academia, tech companies, and other partners to deliver tailored forecasts that can improve human lives. Weather forecasts should be accurate as well as oriented around the specific human needs on the ground, then delivered at the right time and place to inform decisions-like giving farmers advanced notice of the start of the rainy season.

HCWF brings together climate scientists, artificial intelligence (AI) experts, and economists to build and evaluate weather forecasts that can target what citizens need to know, leveraging novel technologies, including AI, and scientific understanding. The interdisciplinary team then works with low- and middle-income countries to test forecast dissemination strategies, refine those strategies based on user response, and scale forecast disseminationto improve decision-making.

Formal employment will be through an in-country employer of record (EoR) under contract with DIL. Additional details regarding salary, benefits, and terms and conditions of employment offered by the EoR will be provided to individuals during the hiring process.

Job Summary:

The Data Scientist will develop data infrastructure, analytical pipelines, and model support systems for the Human-Centered Weather Forecasts initiative and the Development Innovation Lab. As part of a multidisciplinary collaboration between universities, international development agencies, and governmental ministries, the role focuses on processing large-scale observational and forecast datasets, translating weather concepts into robust and reproducible analytical workflows, and supporting the development of publicly available benchmarking and validation systems for forecast products across Indonesia.

Responsibilities:

• Lead or support data science activities including data collection, pipeline establishment, and all analytical needs of research projects.
• Act as a primary point of contact for the establishment and management of project related data pipelines.
• Support the development of models for forecasting different weather phenomena, working closely with atmospheric scientists to translate weather concepts into robust, reproducible analytical workflows.
• Define technical strategies, architect model validation protocols, and mentor other team members on best coding and testing practices.
• Support the development of a publicly available benchmarking and validation system for forecasts.
• Contribute to the design and implementation of A/B testing and field experiment frameworks for forecast dissemination programs.
• Collaborate with researchers for new analyses with large datasets and support data sharing with meteorological agencies and implementing organizations.
• Conduct literature reviews and help write reports and manuscripts.
• Perform other related work as needed.

Minimum Qualifications:

Education:

Master's in data science, climate science, atmospheric science, computer science, statistics, or a related field for the Data Scientist role.

Work Experience:

• Minimum requirements include knowledge and skills developed through 3+ years of work experience in a related job discipline.
• 5+ years of experience is required for the senior data scientist role.
• Experience managing complex data science projects with multiple stakeholders.
• Experience with large-scale geospatial or climate datasets.
• Experience with cloud computing platforms (e.g., AWS, GCP, Azure) and high-performance computing environments.

Preferred Qualifications:

Education:

Ph.D. degree in data science, climate science, atmospheric science, computer science, statistics, or a related field for the senior data scientist role.

Experience:

• Experience managing complex data science projects with multiple stakeholders.
• Experience with large-scale geospatial or climate datasets.
• Experience with cloud computing platforms (e.g., AWS, GCP, Azure) and high-performance computing environments.

Preferred Competencies:

• Strong programming and numerical skills proficiency in Python and SQL.
• Experience with high-performance computing and analysis of large datasets familiarity with distributed computing frameworks (e.g., Dask, Spark).
• Experience with geospatial analysis libraries (e.g., xarray, rasterio, GDAL) and meteorological data formats (NetCDF, GRIB).
• Expertise in weather forecasting, climate modeling/dynamics, or related geospatial applications (preferred).
• Familiarity with theoretical and practical aspects of scientific deep learning and AI weather models (preferred).
• Experience working with Indonesian government agencies (preferred).
• Excellent communication skills and ability to work both independently and as part of a multidisciplinary team.
• Prior work experience in Indonesia, India, Phillipines, Bangladesh, Nigeria, Ethiopia is a plus.

Working Conditions:

This position involves collaboration with international partners and may require travel to field sites in low- and middle-income countries.

Anticipated Salary Range:

252,500,040 - 631,059,390 Indonesia Rupiah/annually

The above salary range represents the Organization's good faith estimate of the possible compensation offer based on the currency of Indonesia for this role at the time of posting.

Benefits Information:

Yes. This position is eligible for benefits in accordance with local Indonesian labor laws. Benefits include, local and private health insurance, travel insurance, annual vacation benefits and public holidays. Additionally, this position is eligible for annual professional development funds and technology support.

AI Statement:

The Development Innovation Lab uses AI-assisted tools to streamline and augment some recruitment processes however, AI is not used to make hiring decisions.