AMI Data Scientist: Predictive Analytics & Insights

Client of Angel Gulf Jobs; Dubai; On-site; AED 180,000 - 340,000; Full time

Job summary

Client of Angel Gulf Jobs is seeking a Data Scientist AMI to analyze Advanced Metering Infrastructure AMI data and develop data-driven solutions to improve utility operations. You will perform predictive analytics, anomaly detection, consumption analysis, and create insights from large smart meter datasets.

The role also involves building dashboards, collaborating with AMI, IT and utility teams, and ensuring data quality while optimizing analytical models.

Qualifications

• Bachelor's or Master's degree in Data Science, Computer Science, Statistics, Engineering, or a related field.
• 3-6 years of experience in Data Science, preferably in AMI, utilities, or smart metering.
• Strong knowledge of Python, SQL, machine learning, and data visualization tools.
• Experience with large datasets, predictive analytics, and statistical modeling.
• Excellent analytical and problem-solving skills.

Responsibilities

• Analyze AMI and smart meter data to identify trends and anomalies.
• Develop predictive models for energy consumption and meter performance.
• Build dashboards and reports to support business decisions.
• Collaborate with AMI IT and utility teams on data-driven initiatives.
• Ensure data quality and optimize analytical models.

Skills

Python

SQL

Machine learning

Data visualization

Large datasets

Predictive analytics

Statistical modeling

Analytical thinking

Education

Bachelor's or Master's in Data Science/CS/Statistics/Engineering

Job description

Client of Angel Gulf Jobs is seeking a Data Scientist AMI to analyze Advanced Metering Infrastructure AMI data and develop data-driven solutions to improve utility operations. You will perform predictive analytics, anomaly detection, consumption analysis, and create insights from large smart meter datasets.

The role also involves building dashboards, collaborating with AMI, IT and utility teams, and ensuring data quality while optimizing analytical models.