Data Scientist - AI / LLM

We are seeking a motivated Data Scientist with AI and Large Language Model experience to join our growing technology team in the USA. This role is ideal for recent graduates or early-career professionals who are passionate about data science, machine learning, artificial intelligence, and LLM-based applications.

The successful candidate will work on real-world AI and data science projects involving data analysis, predictive modelling, natural language processing, generative AI, Retrieval-Augmented Generation, and LLM-powered automation. This is an excellent opportunity for candidates on OPT, CPT, or STEM OPT who want to build strong commercial experience in the AI and data science industry.

Visa Status: STEM OPT/F1-OPT

Design, develop, and evaluate machine learning models for business and customer-focused use cases.

Work with structured and unstructured datasets to identify patterns, trends, insights, and predictive signals.

Build data science solutions using Python, SQL, Pandas, NumPy, Scikit-learn, and related libraries.

Support the development of AI and LLM-based applications using tools and frameworks such as OpenAI, Azure OpenAI, LangChain, Hugging Face, and vector databases.

Assist in building Retrieval-Augmented Generation pipelines using embeddings, document chunking, vector search, and semantic retrieval.

Develop and test prompts for LLM applications, including summarisation, classification, question answering, information extraction, and chatbot workflows.

Collaborate with data engineers, software developers, and business stakeholders to understand requirements and convert them into data-driven solutions.

Perform exploratory data analysis, data cleaning, feature engineering, model training, validation, and performance evaluation.

Work with cloud platforms such as AWS, Azure, or Google Cloud for data storage, AI services, and model deployment.

Create dashboards, reports, and visualisations to communicate insights clearly to technical and non-technical audiences.

Monitor model performance and support improvements to accuracy, reliability, explainability, and responsible AI practices.

Maintain clear documentation of models, datasets, experiments, assumptions, and technical processes.

Bachelor’s or Master’s degree in Data Science, Computer Science, Artificial Intelligence, Machine Learning, Statistics, Mathematics, Engineering, or a related field.

Recent graduate or early-career professional with academic, internship, project, or commercial experience in data science or AI.

Strong understanding of machine learning concepts such as supervised learning, unsupervised learning, classification, regression, clustering, and model evaluation.

Good programming skills in Python.

Good knowledge of SQL for querying and analysing data.

Experience with common data science libraries such as Pandas, NumPy, Scikit-learn, Matplotlib, or similar tools.

Understanding of data preprocessing, feature engineering, model training, and evaluation techniques.

Basic understanding of Large Language Models, Generative AI, NLP, embeddings, vector databases, or RAG pipelines.

Strong analytical thinking and problem-solving skills.

Good communication skills with the ability to explain technical findings in a simple and clear way.