Data Scientist- QA And AI Enablement

Department Icon Data Science Analytics & Machine Learning
149+ Applicants
Posted: 5 months ago
0-1 years
Bengaluru / Bangalore, Karnataka
work from office

Posted: 5 months ago
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Applicants: 149+
Job Description
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Job Description

Job description:
Data Scientist QA & AI Enablement

Role Summary

We are seeking one Data Scientist to join the Hub component of the Client hub-and-spoke engagement model.The Data Scientist will play a key role in supporting the deployment, refinement, and optimization of Coco bots and AI-driven quality engineering initiatives.

Key Responsibilities
  • Participate in daily stand-up meetings, provide status updates, highlight risks, and deliver daily and weekly status reports.

  • Collaborate with business and technical stakeholders to gather representative and high-quality datasets for AI model development and testing.

  • Perform statistical analysis, data visualization, data cleansing, and preparation of datasets for AI/ML testing and validation.

  • Evaluate the effectiveness, reliability, and accuracy of new and existing data sources using appropriate data assessment techniques.

  • Apply predictive modeling techniques to improve QA efficiency and optimize broader business outcomes.

  • Coordinate with cross-functional teams to implement data models and monitor their operational outcomes.

  • Develop and maintain processes, metrics, and tools to continuously monitor model performance, data quality, and accuracy over time.

Required Skills & Experience (Must Haves)
  • AI / Machine Learning: Proficiency level 4/5

  • Predictive Modeling: Proficiency level 4/5

  • Data Modeling Implementation: Proficiency level 3/5

Skills

Data VisualizationData CleansingData ModelingImplementationMachine LearningPredictive ModelingVisualizationAi/mlData ScientistAiMl

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About Company

Defective software can result in lost clients and users, fallen business processes, revenue impacts, security breaches or regulation violation. These risks grow as organizations increase their dependency on software. To mitigate these risks, testing and QA have become an essential part of the success of every software project. Unfortunately most testing and QA miss the critical business context, and instead just focus on the obvious technical risks. This approach does not take into account the bigger picture and does not look at the interrelationship between software testing and business risks.

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Important dates & deadlines?

Application Deadline

19 Jul 26, 01:30 PM IST

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Data Scientist- QA And AI Enablement

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