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Strong employer brand, mid-level generalist data manager role, metro and broad skillset requirements increase competition.
Role requires O2C/SOM domain, ERP, process-mining and automation experience, so industry-specific background is highly important.
Explicit 5–10 years plus 3 years management and many mandatory technical and domain skills makes shortlisting highly strict.
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Lead and manage a team of data scientists and analysts to develop scalable data-driven solutions improving Sales Order Management (SOM) processes globally.
Own the business rules engine strategy, ensuring governance, optimization, and integration of automated decision rules to enhance order quality and reduce defects.
Drive process improvement, automation, predictive analytics, and AI adoption initiatives to increase operational efficiency, reduce cycle times, and support digital transformation within Order-to-Cash operations.
5 to 10 years of experience in Data Science, Advanced Analytics, Process Optimization, or Automation with at least 3 years in people management.
Experience supporting Order-to-Cash (O2C), Sales Order Management, or Customer Operations.
Proficiency in Python, SQL, Pyspark, and data visualization tools (Power BI, Tableau); experience with ML frameworks (Scikit-learn, XGBoost, TensorFlow, or PyTorch); and familiarity with process mining (Celonis), RPA platforms (UiPath, Power Automate, etc.), and ERP systems (Siebel, SAP, Oracle, Salesforce).
Work Experience Required: 5 to 10 years; Notice Period: Not explicitly mentioned in the JD.
Experienced leader capable of managing cross-functional teams in a complex, global financial technology environment focused on operational excellence.
Strong technical expertise in deploying and scaling advanced analytics, AI/ML, and automation within Order-to-Cash or related financial operational workflows.
Proven ability to collaborate with senior stakeholders and business units to translate operational needs into data-driven frameworks that improve business outcomes and adopt emerging AI/LLM technologies.