Business Process Analyst – Automation & Discovery

LSEG · Colombo

Job description – Business Process Analyst – Automation & Discovery

Drive Digital Transformation at LSEG

The London Stock Exchange Group (LSEG) is a global leader in financial markets infrastructure and data, dedicated to driving financial stability and sustainable economic growth. Within our Digitalisation team in DSM (Service Delivery), we are pushing the boundaries of how technology and data optimize global operations. We operate at the intersection of finance and cutting-edge tech, fostering a culture where data-driven insights and innovative engineering collide to solve complex challenges. If you are passionate about being at the forefront of the AI and automation revolution within the capital markets, LSEG offers the global scale and collaborative environment to make a measurable impact.

The Role: Business Process Analyst – Automation & Discovery

As a Business Process Analyst, you will be the primary catalyst for our digital evolution, sitting upstream of engineering to bridge the gap between operational reality and technical execution. Your mission is to dive deep into our service delivery workflows to triangulate truth from system data, process mining, and direct human engagement. You won’t just document “what is”—you will define “what could be” by uncovering hidden inefficiencies and translating them into structured, high-impact use cases for our AI, ML, and Data Engineering teams. This is a discovery-heavy, hands-on role perfect for a curious analyst who enjoys deconstructing complex processes and shaping the roadmap for intelligent automation.

Key Responsibilities

Business Process Analysis

  • 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, not just how it is documented.

  • Engage with SMEs to uncover bottlenecks, challenges, and workarounds not easily visible in system logs.

  • Detect inefficiencies, recurring manual effort, and areas where digital improvements could have real impact.

Data‑Driven Discovery & Insight

  • Use SQL to explore operational datasets and quantify volumes, patterns, exceptions, and constraints.

  • Use Python (e.g., Pandas) for lightweight analytical exploration to support hypothesis testing and prioritisation.

  • Create simple Power BI visualisations to support discovery discussions.

  • Where available, interpret process mining outputs (e.g., Celonis, QPR, 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.

Automation & Use‑Case Discovery

  • Spot areas for workflow and rules‑based automation, analytics enhancements, data‑driven decision support, or ML/AI augmentation (in collaboration with engineering).

  • Assess each potential enhancement using structured criteria including impact, feasibility, suitability, dependencies, and constraints.

  • Translate discoveries into delivery‑ready use cases, including:

    • Clear problem statements

    • Scope and assumptions

    • Expected benefits

    • Risks and constraints

    • Success metrics and value logic

As‑Is → To‑Be Translation

  • Create clear as‑is process maps and to‑be digital/automation concepts (BPMN or equivalent).

  • Clearly 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.

Prioritisation Support

  • Contribute input to a prioritised pipeline of initiatives based on business impact, complexity, dependencies, and readiness.

  • Use simple prioritisation methods (e.g., impact vs effort) to support structured decision‑making.

  • Help determine the most appropriate engineering workstream for each use case.

Operating Model Communication

  • 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.

Adoption & Value Realisation Support

  • 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 vs realised outcomes and capture insights and lessons learned.

  • Contribute to internal narratives articulating the value delivered by Digitalisation.

Collaboration & Continuous Improvement

  • Work closely with DSM Business Services, operational SMEs, 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.

Required Skills & Experience

  • Experience in business process analysis, operational analysis, or continuous improvement roles.

  • Ability to map and clearly explain processes (BPMN, flow diagrams, or equivalent).

  • Working knowledge of SQL for operational data exploration.

  • Basic–intermediate Python (Pandas) for analysis.

  • Confidence engaging with SMEs 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.

Desirable Skills

  • Exposure to process mining concepts (event logs, variants, throughput, conformance).

  • Experience working with or interpreting outputs from tools such as Celonis, QPR ProcessAnalyser, ProM or Power Automate Process Mining (nice‑to‑have, not essential).

  • Experience with Power BI or similar tools for exploratory analysis and insight communication.

  • Experience or interest in business process optimisation or Lean/CI 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.

  • Strong interest in digital transformation and intelligent automation.

Why Your Contribution Matters

By joining LSEG as a Business Process Analyst, you are doing more than just mapping workflows; you are building the foundation for a more resilient and efficient financial ecosystem. We offer a rare opportunity to work directly with AI and ML initiatives while gaining deep exposure to the operational heart of global capital markets. Your work will directly shape the future of DSM, ensuring our engineering efforts are faster to adopt and perfectly aligned with business needs. If you are ready to grow your analytical skills in a high-stakes, high-reward environment where your discoveries become real-world solutions, we want to hear from you.

Home Page

More Related Jobs

To apply for this job please visit lk.linkedin.com.