Hybrid
Full Time
• Lead a team of Data Engineers, Analysts and Data scientists to carry out following activities:
• Connect with internal / external POC to understand the business requirements • Coordinate with right POC to gather all relevant data artifacts, anecdotes, and hypothesis
• Create project plan and sprints for milestones / deliverables
• Spin VM, create and optimize clusters for Data Science workflows
• Create data pipelines to ingest data effectively
• Assure the quality of data with proactive checks and resolve the gaps • Carry out EDA, Feature Engineering & Define performance metrics prior to run relevant ML/DL algorithms
• Research whether similar solutions have been already developed before building ML models
• Create optimized data models to query relevant data efficiently
• Run relevant ML / DL algorithms for business goal seek
• Optimize and validate these ML / DL models to scale
• Create light applications, simulators, and scenario builders to help business consume the end outputs
• Create test cases and test the codes pre-production for possible bugs and resolve these bugs proactively
• Integrate and operationalize the models in client ecosystem
• Document project artifacts and log failures and exceptions.
• Measure, articulate impact of DS projects on business metrics and finetune the workflow based on feedback
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