Job Description

ABOUT JMAN:

JMAN Group is a fast-growing data engineering & data science consultancy. We work primarily with Private Equity Funds and their Portfolio Companies to create commercial value using Data & Artificial Intelligence. In addition, we also work with growth businesses, large corporates, multinationals, and charities.

We are headquartered in London with Offices in New York, London and Chennai. Our team of over 450 people is a unique blend of individuals with skills across commercial consulting, data science and software engineering.

We were founded by cousins Anush Newman (Co-founder & CEO) and Leo Valan (Co-founder & CTO) and have grown rapidly since 2019. In May 2023 we took a minority investment from Baird Capital and in January 2024 we opened an office in New York with the ambition of growing our US business to be as large as, if not bigger than, our European business by 2027.

Why work at JMAN:

Our vision is to ensure JMAN Group is the passport to our team’s future. We want our team to go on a fast-paced, high-growth journey with us – when our people want to do something else, the skills, training, exposure, and values that JMAN has instilled in them should open doors all over the world.

Current Benefits:

Competitive annual bonus
Market-leading private health insurance
Regular company socials
Annual company away days
Extensive training opportunities

Position

Lead the development and implementation of advanced data science models.
Act as a bridge between business requirements and technical execution, ensuring high-quality solution delivery
Mentor junior scientists on coding standards, experimental design, and model ethics
Audit data quality and process integrity across the entire modelling lifecycle.
Mentor and guide junior data scientists.
Stay updated with the latest trends in data science.
Establish the CI/CD pipelines for machine learning, automating the transition from research to production.

Requirements

Advanced proficiency in cloud AI platforms (Vertex AI, SageMaker, or Databricks)
Expertise in MLOps frameworks and LLM orchestration (LangChain/LlamaIndex).
Skilled in Tableau or Power BI for automated reporting and insights
Proficient in Python/R and SQL; experience with TensorFlow/PyTorch;
Deep understanding of supervised/unsupervised learning and Generative AI (LLMs)
Scikit-learn, Pandas, Git, and familiarity with one cloud platform (AWS/Azure/GCP)