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Data Analyst
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Job Title: Data AnalystLocation: BangaloreExperience: 6 yearsAvailable for F2F interview on friday - Yes / NoLocation for drive - Bhive- IndiraNagarRole OverviewWe are seeking a skilled Data Analyst to support our platform powering operationalintelligence across airports and similar sectors. The ideal candidate will haveexperience working with time-series datasets and operational information to uncovertrends, anomalies, and actionable insights. This role will work closely with dataengineers, ML teams, and domain experts to turn raw data into meaningfulintelligence for business and operations stakeholders.
Key ResponsibilitiesAnalyze time-series and sensor data from various sourcesDevelop and maintain dashboards, reports, and visualizations tocommunicate key metrics and trends. Correlate data from multiple systems (vision, weather, flight schedules, etc) toprovide holistic insights. Collaborate with AI/ML teams to support model validation and interpret AI-driven alerts (e.g., anomalies, intrusion detection).
Prepare and clean datasets for analysis and modeling; ensure data qualityand consistency. Work with stakeholders to understand reporting needs and deliver business-oriented outputs. Qualifications & Required SkillsBachelor's or Master's degree in Data Science, Statistics, Computer Science,Engineering, or a related field.5 years of experience in a data analyst role, ideally in a technical/industrialdomain.
Strong SQL skills and proficiency with BI/reporting tools (e.g., Power BI,Tableau, Grafana). Hands-on experience analyzing structured and semi-structured data (JSON,CSV, time-series). Proficiency in Python or R for data manipulation and exploratory analysis.
Understanding of time-series databases or streaming data (e.g., InfluxDB,Kafka, Kinesis). Solid grasp of statistical analysis and anomaly detection methods. Experience working with data from industrial systems or large-scale physicalinfrastructure.
Good-to-Have SkillsDomain experience in airports, smart infrastructure, transportation, orlogistics. Familiarity with data platforms (Snowflake, BigQuery, Custom-built usingopen-source). Exposure to tools like Airflow, Jupyter Notebooks and data qualityframeworks.
Basic understanding of AI/ML workflows and data preparation requirements.