Data & Process Mining Specialist with 4+ years of experience in Celonis, data analysis, and automation. Skilled in Python, SQL, ML, AWS and ETL to deliver actionable insights and process improvements. Currently enhancing…
Data & Process Mining Specialist with 4+ years of experience in Celonis, data analysis, and automation. Skilled in Python, SQL, ML, AWS and ETL to deliver actionable insights and process improvements. Currently enhancing expertise in Signavio, Snowflake, AWS, and GenAI.
Integrated Celonis Process Mining with enterprise ERP systems including ERP and R3 enabling real-time process visibility., Worked on the Procure-to-Pay (P2P) process involving end-to-end data extraction, transformation, and loading (ETL) to support process analytics., Ensured data accuracy and reliability through systematic data cleansing, validation checks, and quality control measures., Collaborated with value leads and business stakeholders to understand requirements and deliver data-driven insights for decision-making., Implemented process improvements using Celonis Action Flows, reducing manual work and improving operational efficiency., Designed and developed multiple P2P dashboards in Celonis using advanced PQL queries to monitor KPIs, detect inefficiencies, and drive cost optimization., Building expertise in Signavio (process modeling), Snowflake (cloud warehousing), and GENAI.
Built a face recognition–based attendance system to replace manual and sheet-based attendance tracking., Designed a user interface using Tkinter and integrated it with backend Python scripts., Implemented a database to store student details, face samples, and attendance logs., Trained face datasets using OpenCV and generated face encodings for accurate verification., Applied methods such as Face Detection, Face Positioning, Face Encoding, and Face Comparison., Automated real-time attendance marking, improving accuracy and reducing manual effort., Ensured high accuracy by validating face matching thresholds and optimizing the model.
Integrated Celonis Process Mining with enterprise ERP systems including ERP and R3 enabling real-time process visibility.
Worked on the Procure-to-Pay (P2P) process involving end-to-end data extraction, transformation, and loading (ETL) to support process analytics.
Ensured data accuracy and reliability through systematic data cleansing, validation checks, and quality control measures.
Collaborated with value leads and business stakeholders to understand requirements and deliver data-driven insights for decision-making.
Implemented process improvements using Celonis Action Flows, reducing manual work and improving operational efficiency.
Designed and developed multiple P2P dashboards in Celonis using advanced PQL queries to monitor KPIs, detect inefficiencies, and drive cost optimization.
Building expertise in Signavio (process modeling), Snowflake (cloud warehousing), and GENAI.
Built a face recognition–based attendance system to replace manual and sheet-based attendance tracking.
Designed a user interface using Tkinter and integrated it with backend Python scripts.
Implemented a database to store student details, face samples, and attendance logs.
Trained face datasets using OpenCV and generated face encodings for accurate verification.
Applied methods such as Face Detection, Face Positioning, Face Encoding, and Face Comparison.
Automated real-time attendance marking, improving accuracy and reducing manual effort.
Ensured high accuracy by validating face matching thresholds and optimizing the model.
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