Under the overall supervision of the Director of the institute, the Predictive Analytics Research Associate undertakes research and outreach activities in support of the institute’s Strategic Plan. The Research Associate’s responsibilities include the following:
Historical and predictive analysis:
Collect, clean, and assess available time series data needed for the institute’s research agenda
Assess/review existing and develop new predictive models and forecasts to further the institute’s research agenda; conduct historical analysis and predictive modeling
Ensure adherence to responsible data standards and guidance
Provide documentation to foster model re-use and integrate data and results on the platform
Policy advice:
Together with partners and key stakeholders define threshold levels for adaptive management and design trigger mechanisms for intervention and use in anticipatory action frameworks
Act as a technical translator to advice decision-makers
Capacity building and training:
Provide documentation, guidance on tools, and training on predictive analytics to researchers in the institute, PhD fellows and partner organizations
Create a community of researchers and practice working on this topic within UNU-MERIT’s Computational Innovation Lab
Mentor junior team members and student researchers/interns if applicable
Outreach and advocacy:
Develop and offer deep dives and events on predictive analytics for climate change, governance, migration and green transformation
Support publication of peer-reviewed publications and develop advocacy materials including posters, presentations and other visual materials
Support funding acquisition
Perform other tasks as assigned by supervisor
Key performance indicators:
Timely and quality delivery of databases
Timely and quality delivery of predictive models and forecasts
Timely and quality delivery of other outputs (dissemination, database development, organization of events, policy advice, etc.)
Timely and quality delivery of inputs to curated fundraising opportunities
Quality and level of engagement with other researchers, teams, consultants, and partners
Quality and level of engagement with partners, related networks and working groups
Qualifications:
Education and certification:
An advanced university degree (Master’s or equivalent, with a preference for a PhD) in a relevant field is required, for instance in computer science, data science, computational social sciences, data analytics & AI or related fields.
Experience and other requirements:
Required:
A minimum of three (3) years of progressively responsible experience working in data analytics, machine learning, AI or other related area
Programming and coding experience (Python, R or an equivalent programming environment), and experience with data visualization software (e.g. Tableau)
Experience in outreach and training activities with students, researchers or policymakers
Demonstrated experience in conducting independent research and analysis
Good team player with strong interpersonal skills demonstrated by the ability to work in a multi-cultural, multi-ethnic environment with sensitivity and respect for diversity
Professionalism, flexibility and ability to work to realistic deadlines, creative thinking, results driven, foreseeing risks and allowing for contingencies when planning
Desirable:
Experience working in multidisciplinary projects between data / innovation and sustainable development / climate change / humanitarian response
Knowledge and experience in addressing societal and policy challenges in the field of (humanitarian) crises, the green transformation or sustainable development
Experience in developing information products to communicate relevant insights to different (societal and policy) stakeholders in different formats (e.g., reports, websites or web-based applications)
Experience in supporting funding acquisition
Experience working with diverse stakeholders including public, private, non-profit and intergovernmental organizations
Language Requirements:
Fluency in English
Knowledge of another UN official working language is an asset, as is knowledge of Dutch.
