Lead Data Scientist

Job Summary

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The Role:

We are seeking a Lead Data Scientist with expertise in large language models for unstructured analysis in international agriculture and food systems. The ideal candidate will have a strong background in data science, machine learning, and natural language processing. They will uncover patterns and insights, creating actionable visualizations, and effectively communicate complex concepts to non-experts. A passion for Generative AI and solving issues like hunger, nutrition, and climate change is essential.

Key Responsibilities:

Apply statistical analysis, machine learning, NLP, deep learning, and generative AI. Collaborate with research teams, conduct needs assessments, and improve models for data classification and extraction. Work with labelled datasets, refine data extraction, and handle unbalanced datasets. Extensive experience with machine learning techniques, open-source libraries, and data science toolkits is required. Fine-tuning transformer-based models, including large language models, is essential.

What You'll Do:

Manage data science projects within a set environment of evidence informed decision making, including defining project objectives, refining existing models, and delivering insights and results to research teams. Analyse large unstructured datasets to extract valuable insights and trends that can inform decisions. Augment and deploy machine learning models to address open-ended issues and improve processes for evidence-informed decision making. Build and train statistical models and machine learning algorithms for replication in future projects. Work with colleagues to support ongoing development of production models and make them available at scale. Collaborate with cross-functional teams of people with diverse backgrounds. Demonstrate independent research skills designed to implement advanced machine learning algorithms and statistical models to solve complex problems. Knowledge about ethical use of AI while experimenting with AI/ML models. Experience with testing and reporting results of AI-models. Establish and manage GitHub repository using best practices.

About You:

Excellent communication and leadership skills, with the ability to effectively collaborate with cross-functional teams. Proven track record of delivering impactful solutions. Experience in analysing complex problems and translating them into data science solutions using machine learning, natural language processing, statistical analysis, and data visualization tools and techniques. Experience with evidence synthesis, impact evaluation, or other assessment programs is preferred. Understanding of the machine learning project lifecycle, tools, and MLOps practices. Hands-on experience in Generative AI, LLM, building RAG applications, and model optimization. Experience with relational databases; Google Big Query preferred. Ability to work in a fast-paced environment. Experience working with applied life sciences experts and/or other scientists.

 Education and Qualification:

Master's Degree in Statistics, Data Science, Computer Science, or relevant quantitative engineering fields (or equivalent combination of education and experience). Minimum of 2 years of data and statistical analysis, preferably with large or unstructured datasets. data science or machine learning engineering experience, including delivering high-quality data science solutions to stakeholders or deploying machine learning solutions into production.

In order to process any applications from nationals outside of the EU and UK, we would require documentation to show the applicant is currently resident and able to work in the in the UK, or is able to relocate on own means and possesses full authorisation from the UK Border Agency (for further information please use the following link http://www.ukba.homeoffice.gov.uk/) Note – we are unable to sponsor or take over sponsorship of an employment Visa. We can provide an Exempt Vignette which will provide right to work; however, this is not sponsorship.

CABI reserves the right to review the applications as they come in on an ongoing basis and close applications once we have found a suitable candidate.

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