Data Analyst

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1. Job Purpose

The Data Analyst is responsible for collecting, analyzing, and interpreting large datasets generated from IoT systems such as fleet tracking, fuel management, and industrial monitoring. The role supports data-driven decision-making by creating dashboards, generating performance reports, and uncovering trends that lead to operational improvements for both clients and internal teams.

2. Key Responsibilities

• Collect, clean, and analyze structured and unstructured data from IoT sensors, GPS trackers, and application platforms.
• Design and maintain interactive dashboards and reports for internal stakeholders and clients using tools such as Power BI or Tableau.
• Monitor key operational KPIs like fuel consumption, idle time, unauthorized usage, route deviation, etc., across various verticals.
• Perform root cause analysis and identify anomalies, inefficiencies, and data-driven opportunities.
• Collaborate with business analysts, developers, and domain experts to support solution development and validation.
• Generate customized client reports periodically (daily/weekly/monthly) as per SLA or project requirements.
• Assist in predictive modeling and statistical analysis to improve automation and forecasting capabilities.
• Document data handling procedures and maintain data integrity across systems.

3. Qualifications & Experience

• Bachelor's degree in data science, Computer Science, Engineering, Statistics, or related field.
• 1–3 years of experience in a Data Analyst or similar role.
• Strong knowledge of data analysis techniques and tools.
• Experience working with large datasets, preferably from IoT or telemetry-based systems.
• Familiarity with SQL, Excel (advanced), Python/R, and BI platforms (Power BI, Tableau, or similar).

4. Required Skills

• Strong analytical and quantitative skills.
• Ability to interpret technical data into business insights.
• Proficiency in data visualization and dashboard creation.
• Excellent communication and documentation skills.
• Basic understanding of IoT data, GPS logs, or machine telemetry.

5. Preferred Skills

• Experience in industrial domains such as fleet, mining, fuel logistics, or manufacturing.
• Knowledge of time-series data and stream processing.
• Exposure to cloud platforms (Azure, AWS, GCP) and IoT data pipelines.
• Familiarity with APIs and JSON/XML data formats.

6. Key Performance Indicators (KPIs)

• Accuracy and timeliness of reports and dashboards.
• Value and relevance of insights provided to clients or management.
• Reduction in manual effort through automation and scripting.
• Data quality improvement and anomaly detection rates.
• Contribution to data-driven decision-making across departments.