AI and Machine Learning Specialist

**Project Overview**

The Humanitarian and Stabilisation Operations Team (HSOT) is contracted by Palladium to deliver the Humanitarian Emergency Response Operations and Stabilisation Programme (HEROS), working with FCDO’s Humanitarian Response Department (HCRD) as well as multiple UK Government teams and partners in 130 countries. The team provides operational and advisory support to meet humanitarian needs and restore stability in sudden-onset disasters and protracted crises.
The Early Warning, Analysis and Reporting team is at the forefront of humanitarian information and analysis, working at the heart of government to inform humanitarian decision-making. The team monitors global events to provide early warning, alerts, and shape humanitarian responses by delivering insights through clear and targeted analytic products. This involves overcoming a challenging information landscape through mixed method approaches as well as developing and improving methodologies that ensures decision-making is grounded in the best available evidence.The Early Warning, Analysis and Reporting (EWAR) team sits at the centre of government humanitarian decision‑making. The team monitors global risks and emerging crises, turning complex, fast‑moving information into timely insights that shape humanitarian action. The team navigates challenging information environments, apply mixed‑method approaches, and continually refine methodologies to ensure decisions are grounded in the strongest available evidence.

**About the Role**

As a Senior Adviser – AI & Machine Learning, you will lead the development and adoption of AI/ML tools that enhance the speed, quality, and clarity of our humanitarian analysis. This includes shaping EWAR’s two‑year AI/ML strategy, building practical tools with colleagues across the Data & Visualisation pillar, and advising on responsible AI/ML uptake across the wider humanitarian community. Your work will be embedded across EWAR’s core workstreams, ensuring innovative methods translate into real‑world impact. The role will be reporting to the TL -Data and Visualisation

**Key Requirements:**

**Strategy**

- Develop the AI / ML strategy for EWAR aligned with the strategic objectives of HCRD and HEROS
- Embed AI/ML approaches into EWAR analytical processes in a proportionate, ethical, and context appropriate manner.
- Stay up to date with AI developments and best practice applications, both in humanitarian communities, wider industry, and across FCDO

**Product Development and Delivery**

- Identify opportunities for EWAR to embed AI tools into its analytical processes, including in the development of the HEWN, scenario development, monitoring evaluation and learning, and in ad hoc analytical products.
- Support with the practical implementation of AI ML technologies; fine tune, evaluate, and deploy AI/ML models for usage in the teams analytical workflows.
- Evaluate and support the continued development of existing AI/ML tools and methodologies used within EWAR.
- Co-design data-driven products that meet FCDO’s humanitarian information needs, as well as operational needs of the HEROS contract
- Once complete and where possible, the AI specialist will provide training for relevant EWAR staff to access and run these tools
- Support the evolution of the HEWN(Humanitarian Early Warning Note) and other flagship products through AI/ML innovation.

**Capacity Building and Knowledge Sharing**

- Ensure responsible AI use amongst EWAR, ensuring compliance with privacy and ethical standards, as well as FCDO responsible use guidelines.
- Regularly communicate limitations of AI/ML methodologies used to non-technical audiences.
- Participation at industry events and active development and maintaining bi-lateral relations with relevant stakeholders. Communicate findings to non-technical audiences.
- Build internal capacity on AI/ML across HSOT, through formal and informal touchpoints.
- Contribute to the development of HSOT's learning agenda and support the Learning and Impact pillar with data for monitoring and evaluation

**Collaboration**

- Work closely with the Data and Visualisation pillar and the wider EWAR team to ensure that all activity is embedded in broader pillar workplan and aligned with the strategic direction of the team.
- Support and contribute to cross-contract AI/ML initiatives and innovation in alignment with the HSOT AI strategy
- Work constructively with colleagues to achieve shared goals.
- Share knowledge, support others, and contribute to a positive team culture.
- Be open to feedback and willing to adapt to meet team needs.

**Risk Management**

- Be aware of potential risks to effective and responsible programme management and contribute to mitigation measures according to job role.
Be familiar with and actively participate in established risk management procedures, including reporting issues against identified risks and failures of mitigation measures.
- Contribute to risk assessment a