Consultant – Forensic Technology, eDiscovery​/Data Analytics

Location
:
Zurich

Work Pattern Percentage
: 80-100%

Deloitte Forensic is one of the largest forensic advisory practices in Switzerland. We provide specialist advice across a broad spectrum of industries on matters such as fraud, anti bribery and corruption, anti money laundering and regulatory investigations. Much of our work is highly sensitive and can attract regulatory scrutiny and media attention.

We are expanding our forensic practice and are seeking talented, highly motivated and innovative practitioners with strong managerial experience in investigations, regulatory enquiries and disputes. Our team is looking for people passionate about seeking and developing a career within eDiscovery, technology-driven investigations, and data management. Knowledge Discovery from unstructured and structured data is our core expertise.

While traditional forensic and eDiscovery activities remain the core of what we do, we also partner on data management and transformation programmes (including M&A related data activities, data separation and contract migration) and on broader regulatory and compliance assignments. To accelerate and augment these workflows, we are investing in GenAI, LLMs and agentic assistants, applying these technologies in a defensible, auditable and secure manner to improve triage, review and insight generation.

• Get the opportunity to be involved in activities where you will be responsible for collecting, preserving and analysing electronic data to help our investigators and legal counsel establish what happened, when it happened, who did it, how they did it, and the extent of the misappropriation or misconduct.
• Your work will primarily involve traditional eDiscovery and computer forensics tasks: assisting with collection of potential evidence from devices and cloud sources, processing and analysing large volumes of emails and other data sources, analysing mobile phone logs and recovering deleted text messages, and helping investigators locate critical documents to crack the case.
• In addition, you will support Discovery & Data Management work streams by helping to build and operate scalable ingestion and processing pipelines, structure diverse data for analysis and contribute to data transformation projects (for example M&A‑related activities, data separation and contract migration). You will also contribute to broader regulatory and compliance engagements as required.
• You will have the opportunity to apply GenAI and LLM capabilities (for example embeddings, vector search, retrieval‑augmented generation, prompt engineering and agentic assistants) and knowledge‑graph techniques to accelerate triage, review and insight generation — always with a focus on defensibility, explainability and secure handling of sensitive material.

Our team will offer you the opportunity to build a strong global professional network and the chance to work on a variety of discovery investigation and data analytics projects. You will be trained in all aspects of our technical disciplines, and will work with an experienced team of forensic professionals who will provide mentoring and direction in developing your career.

• You are technically minded, curious, and have a keen eye for detail. You enjoy taking on responsibility and can handle the pressure of delivering quality results to demanding timescales;
• Solid programming skills, at least proficient in one general‑purpose language (e.g. Python, C#) and one data query language (e.g. T‑SQL); good knowledge of Knowledge Graph modelling or semantic search would be a plus;
• Practical understanding of NLP, generative AI (including LLMs) and agentic AI, with experience of text classification, semantic search, RAG, prompt engineering and agent design, would be an advantage;
• Good knowledge of the usual operating systems (Microsoft Windows, Unix, MacOS) would be a plus;
• You are currently completing, or you are a graduate and have completed your Master’s degree in Computer Science, Natural Science, Engineering or related fields;
• Awareness of chain‑of‑custody, data privacy and model governance…