Data Scientist Manager

Job description

LSEG is one of the world’s leading providers of financial markets infrastructure and delivers financial data, analytics, news and index products to more than 40,000 customers in over 170 countries. We help organization's fund innovation, handle risk and build jobs by partnering with customers at every point in the trade lifecycle: from advising their pre-trade decisions and completing trades to raising capital, clearing and optimization. Data Scientist Manager will lead the design, development, and optimization of data-driven solutions that enhance Sales Order Management (SOM) processes. This role would drive business rules engine program, predictive analytics, AI adoption, workflow automation and operational excellence initiatives that improve order quality, reduce cycle times, and increase automation rates. Successful candidate will combine expertise in data science, process mining, business rules engines, workflow automation, and operational analytics to find improvement opportunities, deliver scalable solutions, and lead a team of data scientists and analysts supporting global Order-to-Cash (O2C) operations. Manage a team of data scientists and analysts supporting global Order-to-Cash (O2C) operations to build scalable solutions, embed intelligence into operational workflows and drive measurable improvements in quality. Key Responsibilities Leadership & Stakeholder Management • Lead and mentor /coach a team of Data Scientists, Change and Quality Specialists • Partner with senior stakeholders Sales, Customer Operations, Finance, Technology, and Compliance teams. • Present recommendations, business cases, and analytical findings to senior leadership. • Drive a data-driven culture across Sales Order Management organization. Business Rules Engine Management • Define and own the strategy for the SOM BRE • Partner with business stakeholders i.e., SOM COE Quality Team, SOM Experts, Finance, DLM to translate operational requirements into automated decision rules. • Establish governance, version control, testing, and audit-ability standards for business rules. • Continuously optimise rule performance through structured monitoring and feedback • Reduce defects and rework by embedding proactive controls earlier in the order lifecycle. Process Improvement & Operational Excellence • Analyze end-to-end processes to identify bottlenecks, inefficiencies, and automation opportunities • Deliver on the Automation and Process Improvement road map for SOM to drive efficiency along with focus on cycle time reduction, quality improvement, and productivity enhancement • Use process mining and operational analytics to identify root causes and drive improvements. • Develop KPI’s and operational dashboards to measure performance of the team Data Science & AI Models • Lead the design and deployment of predictive and prescriptive models to optimise order processing, mitigate risk and improve decision making. • Develop anomaly detection models to identify order quality issues and compliance risks. • Apply appropriate techniques to improve decision-making and exception management. • Drive adoption of advanced analytics, including emerging AI/LLM-based solutions, across SOM operations Automation & Intelligent Operations • Identify opportunities to automate manual processes using machine learning, RPA, and workflow technologies. • Collaborate with process owners, technology teams, and automation developers to implement solutions. • Measure automation effectiveness and drive adoption across operational teams. • Support digital transformation initiatives within Order-to-Cash operations. Experience • 5 to 10 years’ experience in Data Science, Advanced Analytics, Process Optimization, or Automation. • 3 years of people management experience. • Experience supporting Order-to-Cash (O2C), Sales Order Management, Customer Operations. • Proven experience delivering measurable business outcomes through analytics and automation. Technical Skills • Proficiency in Python, SQL, Pyspark and data visualization tools (Power BI, Tableau). • Experience with machine learning frameworks such as Scikit-learn, XGBoost, TensorFlow, or PyTorch. • Knowledge of AWS Glue • Experience with process mining tools such as Celonis or Process Intelligence platforms. • Familiarity with workflow automation and RPA platforms such as UiPath, Power Automate, Automation Anywhere, or Blue Prism. • Experience working with ERP systems such as Siebel, CPQ, SAP, Oracle, Salesforce. LSEG is a leading global financial markets infrastructure and data provider. Our purpose is driving financial stability, empowering economies and enabling customers to create sustainable growth. Our purpose is the foundation on which our culture is built. Our values of Integrity, Partnership, Excellence and Change underpin our purpose and set the standard for everything we do, every day. They go to the heart of who we are and guide our decision making and everyday actions. Working with us means that you will be part of a dynamic organisation of 25,000 people across 65 countries. However, we will value your individuality and enable you to bring your true self to work so you can help enrich our diverse workforce. You will be part of a collaborative and creative culture where we encourage new insights and are committed to sustainability across our global business. You will experience the critical role we have in helping to re-engi