At a Glance
- Tasks: Fine-tune and deploy AI/ML models to enhance humanitarian decision-making.
- Company: Join a leading team at the forefront of government humanitarian action.
- Benefits: Enjoy a competitive salary, hybrid working, and opportunities for professional growth.
- Other info: Collaborative environment with a focus on innovation and ethical AI use.
- Why this job: Make a real difference by using AI to tackle global humanitarian challenges.
- Qualifications: 3+ years in data science or ML engineering; Python and SQL proficiency required.
The predicted salary is between 55000 - 65000 £ per year.
About The Team
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, applies mixed‑method approaches, and continually refines methodologies to ensure decisions are grounded in the strongest available evidence.
About the Role
As a Senior Adviser – AI, fine‑tune, evaluate, and deploy AI/ML models for use in the team's analytic 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 and 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 and FCDO responsible use guidelines.
- Regularly communicate limitations of AI/ML methodologies used to non‑technical audiences.
- Participate at industry events and actively develop and maintain bilateral 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 activities and suggest improvements.
Other Duties
- The post holder will be required to deploy to support an FCDO response if required for up to 25% of the time.
- Undertake any other duties as appropriate to the position, as requested.
- Fulfil role of Duty Officer on rotation, providing week‑long out of hours surveillance of emergencies.
- Contribute to HEROS contract quarterly and annual contractual reporting on specialist portfolio, and provide support as requested in support of results‑based reporting.
- Collaborate constructively with colleagues to achieve shared goals and deliver impactful outcomes.
- Share knowledge and expertise to support team members and contribute to a positive, inclusive team culture.
- Remain open to feedback and demonstrate adaptability to meet evolving team and project needs.
- Support business Transition and Exit Planning: Play a pivotal role in adapting to system upgrades and organisational changes, ensuring the workforce is aligned with future business needs.
- Lead on providing data inputs during the transition phase.
This position follows Palladium’s hybrid working policy, requiring a minimum attendance of three days in the office.
Key Skills And Qualifications
- 3+ years of professional experience in data science, ML engineering, or a similar role.
- Experience creating, testing and rolling out AI/ML tools.
- Experience applying validation methods to assess AI/ML methodologies, including their performance, limitations, and suitability for real‑world application.
- Proficiency in Python and SQL.
- Familiarity with AI/ML workflows, model deployment, and versioning.
- Proficiency in data analysis and visualisation in humanitarian risk analysis, foresight, and early warning.
- Strong communication skills, ability to communicate complex concepts to non‑technical audiences and stakeholders.
- Ability to advise non‑technical stakeholders on the appropriate use and limitations of AI/ML approaches.
- Understanding of data ethics and responsible AI principles, particularly in contexts where accuracy and precision are critical.
- Demonstrated ability to translate complex data into actionable insights and compelling visuals.
- Experience with using Github (or similar) for version control.
- Enthusiasm for working at pace, in collaboration with technical and non-technical colleagues.
- Strategic thinking and ability to align data work with organisational goals.
- Act with integrity, reliability, and respect in all interactions.
- Represent Palladium positively in all professional settings.
- Take ownership of tasks and responsibilities.
- Deliver work to agreed standards and deadlines.
- Follow through on commitments and raise concerns early when issues arise.
- Fluency in English.
Desirable Criteria
- Experience designing and applying analytical frameworks tailored to humanitarian contexts, with demonstrated capacity to drive innovation in analytical frameworks and approaches.
- Experience working with collaborative cloud computing platforms (such as Databricks).
- Advanced degree in Artificial Intelligence, Computer Science, Data Science, Mathematics, Engineering, or a relevant field.
- Experience monitoring and evaluating the impact of data and AI/ML solutions in operational settings.
- Experience with humanitarian early warning systems and risk modelling.
- Experience working in the humanitarian, development, or public sectors.
- Experience supporting an increase in uptake of AI/ML tools in professional settings.
This is a permanent role based in London. Candidates must have the Right to work in the UK and a minimum of 2 years residency in the UK out of the last 5 years to be eligible for this post.
AI and Machine Learning Advisor employer: Palladium: Make It Possible
Palladium International Ltd. is an exceptional employer, offering a dynamic work environment in London where innovation meets humanitarian action. With a strong focus on employee growth, the company provides opportunities for professional development in AI and machine learning, fostering a collaborative culture that values knowledge sharing and adaptability. Employees benefit from a hybrid working policy, competitive remuneration, and the chance to contribute to impactful projects that shape global humanitarian responses.
Contact Details:
Palladium: Make It Possible Recruitment Team
StudySmarter Expert Advice🤫
We think this is how you could land AI and Machine Learning Advisor
✨Tip Number 1
Network like a pro! Get out there and connect with people in the AI and machine learning space. Attend industry events, join online forums, and don’t be shy about reaching out to professionals on LinkedIn. You never know who might have the inside scoop on job openings!
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your AI/ML projects. Whether it’s a GitHub repository or a personal website, make sure potential employers can see what you can do. This is your chance to shine and demonstrate your expertise in a tangible way.
✨Tip Number 3
Prepare for interviews by brushing up on your communication skills. You’ll need to explain complex concepts to non-technical audiences, so practice breaking down your work into simple terms. Mock interviews with friends can help you get comfortable with this.
✨Tip Number 4
Don’t forget to apply through our website! We’ve got some fantastic opportunities waiting for you. Tailor your application to highlight how your experience aligns with the role, especially in humanitarian contexts. Let’s get you that dream job!
We think you need these skills to ace AI and Machine Learning Advisor
Some tips for your application 🫡
Tailor Your Application:Make sure to customise your CV and cover letter to highlight your experience with AI/ML tools and methodologies. We want to see how your skills align with the role, so don’t hold back on showcasing your relevant projects!
Showcase Your Communication Skills:Since you'll be explaining complex concepts to non-technical audiences, it’s crucial to demonstrate your ability to communicate clearly in your application. Use straightforward language and examples that illustrate your knack for making the complicated simple.
Highlight Your Team Spirit:We love a collaborative spirit! Mention any experiences where you worked closely with others to achieve shared goals. This shows us you’re not just about individual success but also about contributing to a positive team culture.
Apply Through Our Website:Don’t forget to submit your application through our website! It’s the best way to ensure we receive all your details correctly and can get back to you as soon as possible. We can’t wait to see what you bring to the table!
How to prepare for a job interview at Palladium: Make It Possible
✨Know Your AI/ML Stuff
Make sure you brush up on your knowledge of AI and machine learning tools, especially those relevant to humanitarian contexts. Be ready to discuss specific models you've worked with, how you've evaluated their performance, and any challenges you've faced in real-world applications.
✨Communicate Clearly
Since you'll need to explain complex concepts to non-technical audiences, practice simplifying your explanations. Use relatable examples to demonstrate how AI/ML can impact humanitarian decision-making, and be prepared to discuss the ethical implications of your work.
✨Show Your Collaborative Spirit
This role involves working closely with various teams, so highlight your teamwork skills. Share examples of how you've successfully collaborated on projects, supported colleagues, and contributed to a positive team culture. Being adaptable and open to feedback is key!
✨Prepare for Real-World Scenarios
Think about potential risks and challenges in deploying AI/ML solutions in humanitarian settings. Be ready to discuss how you've approached risk management in past projects and how you would ensure responsible AI use in this role. This shows you're not just technically savvy but also aware of the broader implications of your work.