Associate, Risk Advisory, Data Analytics

Ankura is a team of excellence founded on innovation and growth.

Our Data Analytics team sits within the Risk Advisory practice, which is one of six practices focused on client delivery services across the Firm.

We help businesses, government entities, and law firms to address their most complex and pressing concerns and make well informed decisions, using some of the most advanced analytics and technology, tools, and techniques.

We are looking for a passionate and technically skilled software engineer to join our Data Analytics team. This is a great opportunity to work on real-world AI projects, including training large language models (LLMs), data modeling, and AI hardware testing. You will also help research, test, and customize advanced AI solutions both on-premise and in the cloud.

• We can support and develop individuals who aspire to be an expert.

• Vast opportunities for career development, with formal development process, training programmes and internal e-learning training platform, Ankura Academy.

• Work with leading experts in an established leading global consultancy.

• Work in a collaborative environment, where our professionals have the freedom to innovate, which promotes curiosity, learning, and communication.

• Assist with project scoping calls and developing work stream process plans.

• Work with the solutions and delivery teams to design, develop, and deploy cutting-edge AI solutions that solve real business challenges and create new opportunities for innovation.

• Assist in testing machine learning models, including LLMs (e.g., GPT, LLaMA, Falcon).

• Identify and assess business problems that can be addressed using AI technologies.

• Conduct comparative research on available ML/LLM models (cloud-based, proprietary, and open source).

• Drive innovation by exploring emerging trends in AI and proposing relevant pilots or proofs-of-concept.

• Provide support in data preparation, preprocessing, and pipeline optimization.

• Conducting quality control checks to ensure accuracy of tasks/deliverables;

• Assist in the preparation of reports, written analyses, trial and other presentations, quantitative exhibits, and other client deliverables; and

• Maintain detailed working records reflecting assumptions, methodologies, and information sources employed during the performance of all analytical tasks.

• Identify, research, and organise information the appropriateness and sufficiency of available data to facilitate effective data access and analysis; and

• Design innovative approaches to solve data related challenges.

• Self and team development

• Responsible for self, peer and Associate task management within a variety of sized projects, including interaction with other team members, professionals from other firms involved in the engagement, and client personnel; and maintain a professional image within the company and project the same to those outside of the company.

• A Science, Mathematical and Quantitative based bachelor’s degree or equivalent. For example, but not limited to Maths, Physics, Engineering, Computer Science etc.

• 1–2 years of hands-on experience in AI/ML related projects. Strictly no vibe coding.

• Knowledge of machine learning principles, neural networks, and data modelling.

• Experience with Python and ML libraries (e.g., scikit-learn, Tensor Flow, PyTorch) is a must.

• Good understanding of ETL processes and experience in manipulating and analysing large amounts of data.

• Interest in AI hardware and performance benchmarking.

• Strong research and analytical skills.

• Strong work ethic, eagerness to learn, and motivation to succeed.

• Experience working in a team-orientated environment.

• Excellent communication (both written and verbal), mathematical, and organisational skills.

• Ability to work both independently and as part of a team in a high‑paced, multi‑task environment with attention to detail.

• Ability to interface with team members and client personnel in demanding, deadline‑driven situations.

• Flexibility with respect to assigned tasks and engagements due to challenging deadlines, changing deliverables, and evolving task priorities.

• Good understanding of enterprise IT infrastructure and…