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Associate Consultant - AI & Advanced technology
Marsh McLennan
Source: Headcount Labs · original listing ↗
Job data: Headcount Labs, ODbL 1.0. Job descriptions belong to their employers.
Source date: 11/4/2026
About this role
We are seeking a talented individual to join our Risk Advanced Technology team at Risk Consulting through our Professional Graduate Programme . This role will be based in Rome for a hybrid role. Risk Consulting is a management consulting firm that provides risk management services as part of Marsh Risk , a leader in insurance brokerage and head of the international Marsh Group, a group of expertise in strategic and management consulting, reinsurance, human capital, and investments. The Risk Advanced Technology practice develops innovative risk management services using advanced technologies (Artificial Intelligence, Machine Learning, Process Mining, and Business Intelligence) to support leading public and private organizations. We will count on you to: Support the application of Machine Learning and AI techniques to analyze risk phenomena across heterogeneous domains (e.g., financial risk, operational risk), detect anomalies/fraud, reduce processing times, and contribute to simplifying business processes with a view to intelligent automation. Contribute to the development of quantitative and financial models, also in the Credit Risk area (e.g., PD, LGD, EAD, Pricing, stress testing, ECL), with the support of more senior professionals and in line with leading market best practices. Perform data analysis, dynamic reporting, risk monitoring dashboards, and early warning systems using Business Intelligence and Advanced Analytics tools. Support clients in developing and evolving risk management frameworks and digital transformation processes. Collaborate in the development of new solutions and methodologies (e.g., Generative AI applied to risk management, explainable ML models, process automation, advanced analytics). Take part in the various project phases: requirements gathering, functional analysis, modeling, implementation, testing, and go-live support. Prepare deliverables, analyses, and project presentations, contributing to the quality of the work and the clarity of communication with the client. Interact with clients and project stakeholders, with team support, presenting analytical evidence and results clearly and effectively. What you need to have: Master’s degree or higher in Management, Management Engineering, Computer Science, Statistics, Financial Mathematics, or related STEM disciplines, with an excellent academic record. Interest in risk management, business processes, and digital transformation Interest and/or solid foundations in one or more of the following areas: Technical skills (vertical) in one or more of the following areas: Data analysis and modeling using Business Intelligence tools (e.g., Power BI). Basic/intermediate knowledge of Machine Learning / AI: supervised and unsupervised models (e.g., classification, regression, clustering, anomaly detection). Familiarity with Credit Risk models and concepts (e.g., PD, LGD, EAD, ECL). Good knowledge of Python for data analysis and automation (e.g., pandas, scikit-learn, openpyxl, or equivalent libraries). Knowledge of Power Platform tools (e.g., Power Apps, Power Automate, Dataverse) is a plus. Basic/intermediate knowledge of relational databases. Management skills (horizontal): Ability to draft project documentation and prepare presentations and deliverables. Strong analytical skills, attention to detail, and a structured approach to problem solving. Strong interpersonal and communication skills, with a collaborative mindset and ability to engage with both technical and non-technical stakeholders. What makes you stand out: Previous experience in consulting, data analytics, risk management, model development, or related fields. Experience, even at an early stage, in developing solutions that combine analytics, Machine Learning, LLMs, and code-based tools (e.g., Python) and/or low-code tools. Familiarity with the banking and credit regulatory context (e.g., Basel framework, CRR, EBA Guidelines/RTS, IFRS 9). Knowledge of Data Visualization and Data Management tools (e.g., Power BI, DAX, SQL, Azure). Knowledge of the main Risk Management frameworks (e.g., ISO 31000, COSO Framework). Interest in Generative AI applications for risk management. Any relevant certifications or training paths in data, risk, analytics, or cloud. What we offer: Tailored career progression : The programme starts with a 6-month internship and €8 meal vouchers per working day, smart working policy and well-being initiatives. At the end of the 6-month internship, based on the tutors' evaluation, the internship can proceed through an apprenticeship contract offering a starting gross annual salary of €28.000. For candidates with prior experience , direct placement into an apprenticeship program will be considered. Additional attractive benefits offered with the apprenticeship contract: insurance coverages, supplementary pension plan, facultative health assistance, flexible benefits, optional stock purchase plan. Further details will be shared during the selection process. Marsh (NYSE: MRSH) is a global leader in risk, reinsurance and capital, people and investments, and management consulting, advising clients in 130 countries. With annual revenue of over $27 billion and more than 95,000 colleagues, Marsh helps build the confidence to thrive through the power of perspective. For more information, visit marsh.com, or follow us on LinkedIn and X. Marsh is committed to providing an inclusive work environment. We aim to attract and retain the best, most qualified people and value colleagues of all backgrounds, without regard to age, background, disability, ethnic origin, family duties, gender orientation or expression, marital status, nationality, parental status, personal or social status, political affiliation, race, religion and beliefs, sex/gender, sexual orientation or expression, skin color, or any other characteristic protected by applicable law. Marsh is committed to hybrid work, which includes the flexibility of working remotely and the collaboration, connections and professional development benefits of working together in the office. All Marsh colleagues are expected to be in their local office or working onsite with clients at least three days per week. Office-based teams will identify at least one “anchor day” per week on which their full team will be together in person.