Graduate Data Scientist I – Aspire Tech Program

About the role

Join the LexisNexis Aspire Graduate Program as a Data Scientist I and work on real‑world AI, machine learning and analytics projects that impact legal technology. You will collaborate with experienced data scientists and engineers, gaining hands‑on experience with data preparation, modeling, visualization, and cloud‑based AI deployment.

Key responsibilities

• Design, develop, and deploy AI solutions alongside data scientists and engineers.
• Analyze large datasets to uncover patterns and trends that guide AI development.
• Collaborate with cross‑functional teams to align AI solutions with business goals and customer needs.
• Evaluate and create new frameworks, defining methodologies and governance.
• Stay informed about emerging technology trends.
• Participate in testing and evaluation of new data‑science tools and technologies.
• Apply statistical analysis, predictive modeling, and pattern‑recognition techniques.
• Support the development and evaluation of machine‑learning and generative‑AI solutions.

Required profile

• On track to receive a bachelor’s or master’s degree in data science, AI, statistics, computer science, computer engineering, or a related field.
• Understanding of core data‑science or machine‑learning concepts with a strong interest in AI‑driven problem solving.
• Experience with large language models and transformer architectures such as BERT, RoBERTa, or T5.
• Knowledge of applying LLMs like ChatGPT, GPT‑3.5, Claude, or Mistral.
• Proficiency with machine‑learning algorithms including deep learning, gradient boosting, and random forests.
• Willingness to learn new technologies and processes.
• Collaborative mindset and solid communication skills.
• Ability to engage with cutting‑edge technologies while working alongside experienced colleagues.

Required skills

• Large language models (LLMs) and transformer architectures (e.g., BERT, RoBERTa, T5).
• Machine‑learning algorithms such as deep learning, gradient boosting, and random forests.
• Generative AI tools (e.g., ChatGPT, GPT‑3.5, Claude, Mistral).
• Statistical analysis, predictive modeling, and pattern‑recognition techniques.
• Cloud technologies and data‑engineering concepts.