Job Description

We provide transactional and digital Opportunity-to-Cash services from lead generation to the collection of incoming payments. We support Siemens businesses in driving top-line growth, profitability, cash conversion and customer intimacy. We are increasing efficiency across different businesses through process reengineering, simplification, digital services and Opportunity-to-Cash integration. We act as one global team, jointly delivering maximum value to our customers as their trusted Partner of Choice by driving E2E processes and digital transformation in an entrepreneurial way.

Change the future with us

• Acquire data from primary or secondary data sources and build data models and deploy to production.
• Supporting existing forecasting, classification projects to further enhance and optimize.
• Identify anomalies/outliers in data, Data cleansing and transformation and getting the data ready for analysis.
• Identify, analyze, and interpret trends or patterns in complex data sets using statistical/visual techniques and provide insights/reports.
• Present the findings or translate the data into an understandable dashboard using visualization (preferred).
• Determine Key performance indicators by studying business functions, gather related data and analyze for insights to improve the KPIs.
• Continuously monitor the business KPIs and alert the management for any inconsistencies.

We don’t need superheroes, just super minds

• Intermediate to expert level proficiency in Python.
• Good understand of AWS platform and have worked with the services like; S3, Athena, Glue and Lambda.
• Working experience in end to end data science project life cycles from use case framing, data collection, data exploration, model building, deployment.
• Strong experience using Machine Learning with supervised, unsupervised & Time series (classification, regression & clustering) algorithms to solve practical business problems.
• NLP, Text Analysis and Data Mining experience.
• Experience with designing end- to- end machine learning systems from scratch for predictive modeling.
• Hands on experience with visualization tools like Power BI, Tableau (Preferred).
• experience of taking Data Science/Machine Learning solutions to production in a commercial environment.
• Exposure to data platforms like SAP HANA, AWS, AZURE.