Coordinate and contribute to the development of knowledge materials, tools and research methodologies, Produce and disseminate original materials, including research briefs, Coordinate with a pool of external contributors and a network of leading international anti-corruption experts, Provide quality control of research project outputs and support the development of relevant knowledge materials by chapters, Contribute to the TI research portfolio by taking part in specified aspects of research project coordination, Support the Research and Knowledge Team on the delivery of specific products and activities, Promote and disseminate TI-S’ knowledge products through various platforms, channels and outreach activities, Generate ideas, develop concept notes/proposals, and activities that are aligned with organisational priorities, Contribute to day-to-day work implementation, including work planning, budget management, monitoring, and reporting, Support the coordination of work and information flow between the Research and Knowledge Team and other internal teams, Stay abreast of developments relating to the area of work and be available to respond to on-demand internal and external stakeholder needs, Represent the organisation at relevant fora within area of expertise as needed, Contribute to the overall functioning of the Research & Knowledge Team by providing proactive and ad hoc support where necessary

Market Research & Analysis: Conduct in-depth market research to identify opportunities for new initiatives, programs, and nonprofit ventures., Data Analysis: Perform quantitative and qualitative research into the food system transformation space, analyzing data from multiple sources to identify trends and advocacy opportunities., Idea Development: Translate research findings into concrete ideas and areas for launching impactful initiatives through the Kickstarting for Good program., Reporting: Consolidate research findings into structured reports, presentations, and action plans for internal and external stakeholders., Stakeholder Engagement: Assist in research-related outreach to funders, mentors, and partners, and contribute to discussions on platforms such as HIVE, EA Forum, and FAST Forum., Surveys & Interviews: Conduct surveys and interviews with key stakeholders (funders, mentors, founders) to identify gaps and opportunities in the movement., Strategic Planning: Design and implement an effective approach to developing and validating new ideas for the program., Program Evaluation: Assess feedback from previous years, extract key learnings, and recommend improvements for future iterations of Kickstarting for Good., Participant Support: Help Kickstarting for Good participants and graduates validate their ideas by measuring impact and conducting targeted market research.

Identify promising new directions based on the scientific literature, results from in-house experiments, and your own novel ideas., Turn these ideas into reality by describing, presenting, designing, implementing, and experimenting with novel machine learning architectures, models, and variants of existing models, Analyze experiments that you and others run, and form ideas and hypotheses to explain results, Run large-scale distributed machine learning experiments, Work with the Staff Data Science team and with other teams involved in machine learning and translational research, Resolve technical difficulties that arise as part of the data science and machine learning work, Develop ideas about our data science and machine learning strategy, and how this relates to business objectives, so as to provide a competitive advantage, Develop ideas about product management on technical and scientific feasibility and risks of complex product features, Contribute to technical and scientific design, planning, and integration of our platform across systems and algorithms, Provide technical and scientific guidance in data science model, algorithm, and system design reviews, Educate mid-level and junior ML researchers and data scientists to bring them up to the next level, Demonstrate long-term thinking and utmost technical and scientific excellence in your individual contributions, Support data science teams in maintaining up-to-date, high-quality documentation and code