Job Description
About the job DATA ANALYSTS (MANUFACTURING)
Job Description: We are seeking an experienced Data Analyst with strong skills in Python, Databricks, computer vision, SQL, and Azure, combined with a solid background in manufacturing. The ideal candidate will have over 6 years of experience working with large datasets, analyzing production data, and applying advanced analytics and machine learning techniques to improve manufacturing processes.
Key Responsibilities:
- Analyze and interpret complex manufacturing data using Python, Databricks, and SQL to drive insights and optimize production processes.
- Develop and implement computer vision models for defect detection, process optimization, and quality control in a manufacturing environment.
- Collaborate with cross-functional teams to integrate data from IoT devices, sensors, and control systems into Azure-based data pipelines.
- Create visualizations and dashboards to monitor key performance indicators (KPIs) and track manufacturing performance.
- Perform data modeling, cleansing, and transformation to ensure accurate and meaningful analysis of manufacturing datasets.
- Utilize Azure cloud services to build scalable and secure data solutions for manufacturing analytics.
- Apply machine learning and predictive analytics techniques to enhance manufacturing efficiency, reduce downtime, and improve product quality.
Requirements:
- 6+ years of experience as a Data Analyst, with a focus on Python, Databricks, SQL, and Azure in manufacturing environments.
- Experience with computer vision applications in manufacturing for process monitoring and quality control.
- Strong knowledge of data analytics, statistical modeling, and machine learning techniques.
- Proven ability to work with large datasets from industrial control systems and IoT devices.
Vertical:
Technology
Job Details
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Job Location
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Bengaluru India
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Company Industry
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Other Business Support Services
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Company Type
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Unspecified
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Employment Type
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Unspecified
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Monthly Salary Range
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Unspecified
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Number of Vacancies
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Unspecified