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Tier-1 brand, metro Bangalore, mid-level generalist title, and broad technical plus domain requirements increase competition.
Requires Order-to-Cash domain and process-mining expertise, so moderately sensitive to industry background.
Explicit 5–10 years, 3 years people management, and mandatory technical/domain stack create strict shortlisting filters.
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Lead a team of data scientists and analysts to develop scalable data-driven solutions improving Sales Order Management processes and global Order-to-Cash operations.
Own and drive the business rules engine strategy including governance, monitoring, and optimization to enhance order quality and reduce cycle times.
Lead deployment of predictive analytics, AI models, automation and workflow enhancements to increase operational efficiency and automation rates.
5 to 10 years experience in Data Science, Advanced Analytics, Process Optimization, or Automation; including 3 years in people management.
Experience supporting Order-to-Cash, Sales Order Management, or Customer Operations.
Proficiency in Python, SQL, Pyspark; experience with machine learning frameworks (Scikit-learn, XGBoost, TensorFlow, PyTorch).
Familiarity with process mining tools (e.g., Celonis), workflow automation/RPA platforms (UiPath, Power Automate, etc.), and ERP systems (Siebel, CPQ, SAP, Oracle, Salesforce).
Experienced leader managing data science teams delivering measurable business impact in Sales Order Management or Order-to-Cash domains.
Strategic thinker capable of aligning technology solutions (AI, automation, business rules engines) with operational excellence goals.
Strong cross-functional collaboration skills managing stakeholders across Sales, Finance, Technology, and Compliance to drive adoption of data-driven initiatives.