Assistant Manager / Manager, Data Scientist, Simulation and Insights, Strategy & Business Design

Overview

In this Data Scientist role within Deloitte’s Simulation & Insights team, you will build and maintain data science, AI, and simulation models to drive business outcomes for clients. You will work with a multidisciplinary group to translate technical results into impactful presentations for non-technical audiences and contribute to innovative, data-driven solutions. You’ll apply ML/AI techniques on structured and unstructured data and stay ahead of emerging technologies. This is a hands-on, impact-focused role with opportunities to mentor others and shape client outcomes.

Pay / Benefits

• hybrid working (Deloitte Works)
• return-to-work coaching and support
• world-class development and training
• focus on well-being and inclusion
• collaborative culture
• career growth opportunities

Responsibilities

• Apply data science, ML, and AI techniques to extract insights and deliver business value from data
• Develop and maintain data science, AI, or simulation models in Python
• Collaborate with stakeholders to understand challenges, capture requirements, and present findings visually
• Stay abreast of emerging technologies and best practices to drive team innovation
• Utilise AI tooling in day-to-day work and contribute to model development, deployment, and monitoring

Key requirements

• Strong academic background in a STEM subject
• High level problem solving, analytical and creative thinking
• Strong foundation in statistics, probability, and data analysis
• Hands-on experience in data science, ML, and AI with delivering solutions
• Hands-on experience with LLMs (RAG, fine-tuning, agentic AI architectures); familiarity with MCP and A2A communication frameworks
• Proficiency in Python and common data science libraries (NumPy, Pandas, SciPy)
• Experience with AI tools/platforms for model development and deployment (GitHub Copilot, Databricks, MLFlow)
• Understanding of code quality, collaboration, and reproducibility
• Ability to communicate technical information to non-technical audiences and present findings clearly
• Experience working in multidisciplinary teams and building client relationships
• Commitment to staying up-to-date with emerging technologies and practices

• Strong communication to non-technical audiences
• Collaborative mindset and relationship-building
• Creative problem solving
• Python and data science libraries (NumPy, Pandas, SciPy)
• ML/AI techniques and model development
• LLMs, RAG, fine-tuning, agentic AI architectures

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