Role Description GPN Recruitment are delighted to be working with a leading professional services firm seeking an experienced Forensic Accountant to join their specialist investigations team on an interim basis. This is an excellent opportunity to work on a high-profile, large-scale engagement involving complex financial analysis, claimant interviews, and detailed report writing. This is a remote contract with an immediate start, offering the opportunity to work alongside an experienced forensic team on meaningful and impactful assignments. - Conduct forensic accounting investigations across complex financial matters. - Review and analyse financial records to quantify financial losses. - Reconstruct financial information from incomplete or fragmented records. - Conduct interviews with claimants in a professional, sensitive and empathetic manner. - Prepare clear, accurate and well-structured forensic reports to support legal and compensation processes. - Analyse large datasets and identify financial anomalies or inconsistencies. - Liaise with legal professionals and internal stakeholders throughout the lifecycle of each case. - Maintain comprehensive working papers and ensure all findings are fully evidenced. - Manage multiple cases simultaneously whilst meeting strict deadlines. Qualifications - Previous forensic accounting or financial investigations experience. - Report writing experience would be ideal. - Ideally to have experience conducting interviews or gathering evidence as part of investigations. - Excellent analytical skills with advanced Excel capability. - Experience reviewing complex financial records and performing detailed reconciliations. - Strong attention to detail and investigative mindset. - Excellent written and verbal communication skills. - Ability to work independently in a fully remote environment. - Immediate availability or short notice preferred. Benefits - Fully remote working. - Immediate start. - Competitive hourly rate. - Opportunity to work on a significant, high-profile forensic engagement. - Exposure to complex investigative and legal support work. - Collaborative and highly experienced forensic team. - Potential for contract extension based on project requirements.

• Lead forecasting initiatives by designing and implementing advanced time series models to predict sales and behavioural trends for thousands of customers. • Develop scalable machine learning solutions that power real-time decision-making across risk management, fraud detection, and product personalization. • Collaborate cross-functionally with product managers, engineers, and business stakeholders to translate complex data challenges into actionable insights and measurable business outcomes. • Drive innovation in fintech applications by experimenting with cutting-edge approaches (e.g., deep learning architectures, probabilistic forecasting, and transformer-based models). • Ensure compliance and transparency in model development, aligning with industry regulations and ethical standards for financial data usage. • Shape the data science strategy by identifying opportunities where predictive modeling can unlock new value streams and competitive advantages.

• Own and evolve the product vision, strategy, and roadmap for MarketSmart • Define clear priorities and success metrics to guide roadmap decisions • Lead ongoing product discovery to understand customer workflows and pain points • Translate customer, market, and performance insights into product requirements • Collaborate with Engineering and Product Design to define and deliver solutions • Analyze product usage data, campaign performance metrics, and customer feedback • Lead validation efforts including beta programs, usability testing, and post-launch feedback

• Advise research and engineering teams on statistical methodologies, experimental design, predictive modeling, and analytical best practices. • Help improve AI model performance across data science, analytics, and machine learning domains. • Create complex, real-world data science tasks that test quantitative reasoning, statistical thinking, and machine learning knowledge. • Develop accurate, well-structured solutions that reflect industry best practices. • Review and assess analytical solutions generated by AI systems and subject matter experts. • Identify errors, inconsistencies, flawed assumptions, and opportunities for improvement. • Provide clear, actionable feedback to enhance model quality and reasoning capabilities. • Build scoring rubrics and evaluation methodologies for: • Statistical reasoning • Predictive modeling • Machine learning workflows • Data interpretation • Experimental design • Business analytics and decision-making • Ensure consistent quality standards across datasets and evaluation processes. • Work closely with AI researchers, engineers, and domain experts to maintain accuracy, consistency, and rigor in training data development.