The prospect
As a Staff Data Analyst, you will support multiple business and engineering teams by delivering advanced data analyses, reporting, and data visualization solutions. You will work closely with stakeholders to understand business questions, translate requirements into analytical approaches, and communicate insights in a clear and structured way. The role combines hands‑on analysis with the opportunity to contribute to reusable tools, dashboards, and data preparation processes that support ongoing analytics and data science initiatives within the Tire Intelligence organization.
On this position you will:
- Conduct advanced data analyses to address a range of business and engineering questions
- Design, develop, and maintain end‑to‑end data visualization dashboards to support decision‑making
- Prepare clear, structured documentation summarizing analytical findings and recommended actions
- Translate business requirements into practical data analysis and reporting solutions
- Coordinate recurring KPI generation and reporting activities,
ensuring consistency and data quality
- Develop and maintain custom data preparation solutions to support machine learning initiatives, including data exploration, cleaning, visualization, and annotation
- Collaborate with data scientists and other technical teams to support analytics and modeling workflows
- Stay informed about developments in data analytics technologies and methods to provide relevant support and recommendations
- Provide guidance and coaching to junior data analysts and support internship activities
- Comply with internal systems, data governance standards, and technical constraints
Skills & Qualifications:
Demonstrated experience with:
- Developing advanced analytics solutions on large data sets to support data-driven decisions
- Designing and delivering data visualization dashboards
- Automation of reports and KPI generation
- Experience with IoT and sensor data is an asset
Demonstrated knowledge o
📌 Staff data analyst (Hyderabad)
🏢 A3R0-GTCI
📍 Hyderabad
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