Data Scientist - AI

HCLTech; Greater London; On-site; GBP 90,000 - 120,000; Full time

Job summary

HCLTech seeks a skilled data engineering specialist to extract insights from complex datasets and drive AI-ready solutions. You will collaborate across teams, asking the right questions and applying scale-driven analytics to deliver impactful results.

The role emphasizes MLOps, responsible AI practices, and hands-on work with contemporary AI frameworks and cloud services in a fast-paced, learning-focused environment.

Qualifications

• Strong commercial experience in Python development for data science and ML applications.
• Proven experience with Generative AI models and LLMs.
• Hands-on cloud platform experience (AWS and/or Azure).
• 1–2 years in quantitative analytics or data modeling.
• Deep understanding of predictive modeling and ML techniques.
• Fluency in Python, C/C++, Java and SQL.
• Familiarity with Cassandra, Hadoop, Spark, Tableau.
• Knowledge of MLOps, AI governance and responsible AI.
• Experience with LangChain, Hugging Face, OpenAI, Bedrock, Azure AI Services.
• Knowledge of Docker and Kubernetes.

Skills

Python

Generative AI models

ML

Predictive modeling

C/C++

Java

SQL

MLOps

AI governance

LangChain

Hugging Face

OpenAI

Bedrock

Azure AI Services

AWS

Docker

Kubernetes

Cassandra

Hadoop

Spark

Tableau

Tools

LangChain

Hugging Face

OpenAI

Bedrock

Azure AI Services

Docker

Kubernetes

AWS

Azure

Cassandra

Hadoop

Spark

Tableau

Job description

The ideal candidate's favorite words are learning, data, scale, and agility. You will leverage your strong collaboration skills and ability to extract valuable insights from highly complex data sets to ask the right questions and find the right answers.

Required Skills and Qualifications

• Strong commercial experience in Python development for data science and machine learning applications.
• Proven experience working with Generative AI models, including Large Language Models (LLMs) and AI-powered solutions.
• Knowledge and hands-on experience with cloud platforms, preferably AWS and/or Microsoft Azure.
• At least 1 - 2 years' of experience in quantitative analytics or data modeling
• Deep understanding of predictive modeling, machine-learning, clustering and classification techniques, and algorithms
• Fluency in a programming language (Python, C,C++, Java, SQL)
• Familiarity with Big Data frameworks and visualization tools (Cassandra, Hadoop, Spark, Tableau)
• Familiarity with MLOps, AI governance, and responsible AI practices.
• Experience with modern AI frameworks and tooling such as LangChain, Hugging Face, OpenAI, Bedrock, Azure AI Services, or similar technologies.
• Knowledge of containerization and deployment technologies such as Docker and Kubernetes.