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

Keyskills: Predictive Modeling Data Science Generative Ai Artificial Intelligence Time Series Analysis Natural Language Processing Statistical Modeling Machine Learning Deep Learning Python Ml Predictive Analytics
Tredence is a global data science solutions provider focused on solving the last mile problem in AI. The last mileis the gap between insight creation and value realization.Headquartered in San Jose, the company embraces a vertical-first approach and an ou