As professionals in FTI Consulting’s Forensic & Litigation Consulting practice, we are involved in complex, global and high-profile litigation, arbitration and investigations combining end-to-end risk advisory, investigative and disputes expertise to deliver holistic solutions for our clients.
Consultants within the Data & Analytics (D&A) team support this by providing advanced analytics and delivering strategic business solutions for client matters involving large and disparate sets of financial, operational and transactional data. Our objective is to make data tell a story, revealing truths underlying commercial disputes, regulatory inquiries and operational activities.
The D&A team are looking for analytical students to join us for a summer internship programme in London from July to August 2023. This Future Leaders internship programme is an in-person internship for those who self-identify as Black ethnic minority background with a strong interest in a career in Data & Analytics.
A large financial institution faced the task of investigating its customers' activity to assess to what extent any business was being conducted with sanctioned entities. D&A employed the use of name screening methods and built a data processing pipeline to extract, analyse and present information to its deployed review platform, enabling the investigation.
D&A were retained by a law firm to support an independent review panel, set up to investigate the extent of match fixing within the sport of tennis. The team collated multiple disparate sources of match data and supplemented it with suspicious match alerts to analyse and isolate demographics which displayed the highest likelihood of match fixing. To do this the team combined statistical techniques with Tableau visual analytics.
Lawyers facing the review of millions of documents were looking to augment existing tools with a bespoke algorithm, tailored to their specific needs. D&A built a cutting-edge natural language processing pipeline to separate the relevant information from the noise in the data via the use of pre-trained base models for transfer learning.
A Silicon Valley ride hailing startup was looking to optimise their strategy of achieving a 100% EV fleet by 2025. D&A developed a suite of a simulation tools as well as a genetic algorithm powered optimisation technique to identify optimal locations for new charging stations and for expanding existing charging stations.
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