What we do
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.
Example projects:
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.
What You Will Do
- Identify, acquire, integrate and analyse diverse and voluminous client data
- Develop analytical solutions to client problems using a range of algorithms and tools
- Design and implement complex data models incorporating both private and publicly available data to facilitate analysis
- Provide tailored machine learning solutions to solve complex business problems across different domains. Projects range from proof of concepts to long-term productionised pipelines in such diverse areas as anomaly detection, geo-spatial modelling, natural language processing, clustering, network analysis, etc.
- Work both with senior elements and directly with clients and stakeholders to understand and identify their requirements
- Perform analytical work, individually and in project teams
- Guarantee the quality of the delivered work, by performing quality control checks and quality control documentation
- Implement and run data tasks such as: data analysis, predictive analysis, data visualisation
What we offer you
- The opportunity to be a part of dynamic and challenging engagements that appear on the news and have impacts measured in the billions of dollars
- Access to a wide range of training and development opportunities, to develop skills and gain accreditation where applicable
- The ability to work with and learn from experts across various fields, including anti-money laundering, sanctions, financial analysis and more
- Direct exposure to clients and stakeholders from different industries and backgrounds
- A depth and breadth of understanding of the suite of tools used for data analysis, modelling, and visualisation
- A well-defined career path with regular appraisals and professional guidance
How to apply
Round 1 – Online Application
Please provide CV and cover letter in your application.
Round 2 – Online Assessment
Round 3 – Assessment Centre/Interviews
Requirements
Graduate Scheme Requirements:
- Bachelor’s degree in a STEM subject or related discipline
- Operational knowledge of relational databases and SQL language
- Experience with programming/scripting languages such Python, VBA or equivalent
- A passion for problem-solving and strong analytical skills
- The ability to perform in demanding, deadline-driven situations
- Excellent communication, interpersonal and organisational skills
- The ability and willingness to travel at short notice
- Knowledge of general machine learning concepts advantageous (training/test, cross-validation, supervised/unsupervised learning, regression and classification, clustering, over/under-fitting, ensemble methods, dimension reduction and feature extraction)
Summer internship requirements:
- Penultimate year of a degree in a STEM subject or related discipline
- Operational knowledge of relational databases and SQL language
- Experience with programming/scripting languages such Python, VBA or equivalent
- A passion for problem-solving and strong analytical skills
- The ability to perform in demanding, deadline-orientated situations
- Excellent communication, interpersonal and organisational skills
- Knowledge of general machine learning concepts advantageous (training/test, cross-validation, supervised/unsupervised learning, regression and classification, clustering, over/under-fitting, ensemble methods, dimension reduction and feature extraction)
