Operational Risk Manager Assistant

The 'Operational Risk Manager Assistant' role is part of SCOR's ORM team. ORM supports the
identification, assessment and monitoring of operational risks across the Group, including governance
and reporting, coordination with subject matter experts, and continuous improvement of the operational
risk scenario framework. Scenarios are structured narratives of plausible operational loss events; they
are documented consistently, reviewed with experts and committees, and translated into quantitative
assessments (frequency/severity assumptions) that notably serve as key inputs to the Operational Risk
Model.

As a leading global reinsurer, SCOR offers its clients a diversified and innovative range of reinsurance and insurance solutions and services to control and manage risk. Applying "The Art & Science of Risk," SCOR uses its industry-recognized expertise and cutting-edge financial solutions to serve its clients and contribute to the welfare and resilience of society in around 160 countries worldwide.

Working at SCOR means engaging with some of the best minds in the industry - actuaries, data scientists, underwriters, risk modelers, engineers, and many others - as we work together to find solutions to pressing challenges facing societies.

As an international company, our common culture is defined by "The SCOR Way." Serving both to build momentum that drives the Group forward and as a compass to guide our actions and choices, The SCOR Way is anchored by five core values, reflecting the input of employees at all levels of the Group. We care about clients, people, and societies. We perform with integrity. We act with courage. We encourage open minds. And we thrive through collaboration.

SCOR supports inclusion and the diversity of talents, and all positions are open to people with disabilities.

The Working Student will support the enhancement and operationalisation of the Group Operational
Risk Scenario framework, with a focus on improving the structure, consistency, documentation and
analytical support for scenario assessments used as key inputs to the Operational Risk Model. This
includes supporting the evolution towards a more structured scenario universe (e.g., "scenario
families"), improving scenario data quality, and preparing materials to facilitate reviews with subject
matter experts and governance committees.
We are looking for a candidate available at least 12 months, ideally longer.

Responsibilities

Key duties and responsibilities

• Scenario framework enhancement & documentation
  Support the design and documentation of an improved scenario framework (e.g., structuring scenarios
  into families and defining aggregation principles). Maintain and improve scenario documentation
  standards (definitions, assumptions, net-of-controls logic, traceability of changes). Help ensure
  scenarios remain coherent and integrated within the broader scenario universe

• Scenario inventory, data quality & change control
  Consolidate scenario inventories (IDs, owners, risk taxonomy mapping, versioning, review dates), and highlight gaps, overlaps or inconsistencies. Perform quality checks on key scenario fields (severityranges, frequencies, time horizons, documentation completeness) and propose standardised
  improvements.

• Analytical support for scenario calibration
  Produce basic analytics and visual summaries to support scenario calibration discussions (e.g.,
  distributions, sensitivity views, comparisons across years / scenario families). (Analytical support
  aligned with scenario assessment process.) Support preparation of scenario review packs for
  workshops with SMEs / first line stakeholders (templates, pre-reads, action logs).

• Governance support deliverables
  Help prepare concise documentation and slides for internal governance touchpoints and committees when scenario framework topics are discussed. Track decisions, action items and follow-ups related to scenario framework improvements and scenario updates.

Qualifications

Required experience & competencies

Technical / Analytical

• Strong analytical skills; ability combine multiple frameworks and structure messy information into clear
  frameworks. Comfort with quantitative reasoning (ranges, frequencies, distributions) and data quality
  checks. Proficiency in PowerBI and MS suite (excel, word, ppt). Ability to use AI is strongly
  recommended.

• Knowledge of statistics / modelling concepts; or programming skills (Python/R) for data processing.

Soft skills

• Strong written communication (ability to draft crisp notes and slide content).

• Reliability, attention to detail, and respect of confidentiality. Ability to work with multiple stakeholders (ORM team, SMEs, first line) in a professional setting