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LSEG

Global financial market infrastructure and data

Business Process Analyst - Automation & Discovery

Business AnalysisConfirmed live in the last 24 hours
Full-timeLondon, UKNo salary listedIn-person

About the Job

Requirements

  • Experience in business process analysis, operational analysis, or continuous improvement roles.
  • Ability to map and clearly explain processes using BPMN, flow diagrams, or an equivalent method.
  • Working knowledge of SQL for operational data exploration.
  • Basic-to-intermediate Python, including Pandas, for analysis.
  • Confidence engaging with subject matter experts to understand real workflows and recurring issues.
  • Ability to convert qualitative and quantitative insights into structured use-case documentation.
  • Ability to create clear presentation materials for business and non-technical groups.
  • Experience in Agile or iterative environments.

Responsibilities

  • Analyse end-to-end operational workflows, including manual steps, handoffs, approvals, exceptions, and rework loops.
  • Combine process artefacts, interviews, and direct operational insight to understand how work is performed in practice, rather than relying only on documentation.
  • Engage with subject matter experts to uncover bottlenecks, challenges, and workarounds not easily visible in system logs.
  • Detect inefficiencies, recurring manual effort, and opportunities for digital improvements.
  • Use SQL to explore operational datasets and quantify volumes, patterns, exceptions, and constraints.
  • Use Python, including Pandas, for lightweight analytical exploration to support hypothesis testing and prioritisation.
  • Create simple Power BI visualisations to support discovery discussions.
  • Interpret available process-mining outputs, such as Celonis, QPR, or Power Automate Process Mining, to validate real-world execution paths and uncover hidden variants.
  • Combine qualitative process understanding with quantitative insight to strengthen use-case discovery.
  • Identify opportunities for workflow and rules-based automation, analytics enhancements, data-driven decision support, or machine-learning and AI augmentation in collaboration with engineering.
  • Assess potential enhancements using structured criteria, including impact, feasibility, suitability, dependencies, and constraints.
  • Support the Digitalisation intake, discovery, and assessment process by ensuring opportunities are consistently evaluated, documented, and prioritised before delivery.
  • Quantify expected business value, effort, complexity, and implementation considerations to support prioritisation decisions.
  • Translate discoveries into delivery-ready use cases with clear problem statements, scope and assumptions, expected benefits, risks and constraints, success metrics, and value logic.
  • Define and baseline operational key performance indicators to support opportunity assessment and post-implementation value tracking.
  • Create clear as-is process maps and to-be digital or automation concepts using BPMN or an equivalent method.
  • Articulate what will change, what will remain, and where automation or AI will be applied.
  • Provide contextualised, well-scoped inputs to engineering teams to support effective design and delivery.
  • Contribute input to a prioritised pipeline of initiatives based on business impact, complexity, dependencies, and readiness.
  • Use simple prioritisation methods, such as impact versus effort, to support structured decision-making.
  • Help determine the most appropriate engineering workstream for each use case.
  • Produce clear, concise visualisations of processes, operating models, and future-state workflows.
  • Prepare communication materials and presentations that explain use cases, benefits, and expected changes in accessible, non-technical language.
  • Support alignment sessions by helping teams understand how processes and roles may evolve.
  • Identify potential change impacts early in the lifecycle to support smoother solution adoption.
  • Act as a feedback channel between business users and engineering teams during early rollout.
  • Track intended versus realised outcomes and capture insights and lessons learned.
  • Contribute to internal narratives that articulate the value delivered by Digitalisation.
  • Work closely with DSM Business Services, operational subject matter experts, Business Architects, and engineering teams.
  • Maintain a structured view of analysed processes and discovered enhancements.
  • Contribute to improving templates, discovery approaches, prioritisation methods, and ways of working.

Desired Qualifications

  • Exposure to process-mining concepts, including event logs, variants, throughput, and conformance.
  • Experience working with or interpreting outputs from Celonis, QPR ProcessAnalyser, ProM, or Power Automate Process Mining.
  • Experience with Power BI or similar tools for exploratory analysis and insight communication.
  • Experience or interest in business process optimisation or Lean and continuous improvement approaches.
  • Exposure to automation, analytics, machine learning, or AI initiatives.
  • Ability to interpret operational metrics to support prioritisation.
  • Experience in regulated or operationally complex environments.
  • Experience working within Capital Markets, Financial Services, Operations, Post Trade, Market Data, or other regulated environments.

About the Company

LSEG

Global financial market infrastructure and data

LSEG provides global financial market infrastructure and data across the full value chain. It delivers data, analytics, and risk-management tools, benchmarks via FTSE Russell, regulatory and financial crime risk services, and trading, clearing, and settlement through its Capital Markets and Post Trade divisions, typically accessed via subscriptions, licensing, and fees. The company differentiates itself by offering an integrated, end-to-end platform that covers pre-trade data and analytics to post-trade processing with a broad, global footprint. Its goal is to grow over the long term by leveraging its diversified portfolio and international reach to create value for shareholders and customers.

Company size
10,001+
Company stage
IPO
Headquarters
London, United Kingdom
Founded
1801

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