Data Analyst
Bangalore, India - Remote, Overlap specifically for the first two hours of business everyday with the team in the MT zone.Full-TimeMiddle
Salary not disclosed
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Job Details
- Experience
- 3–5 years of overall experience, including relevant internships; 1–3 years of relevant experience across full-time roles and internships in data analytics, product analytics, data science or a related field.
- Required Skills
- PythonSQLMachine LearningSnowflakeTableauProduct AnalyticsData scienceData analyticsDatabricks
Requirements
- 1–3 years of relevant experience across full-time roles and internships in data analytics, product analytics, data science or a related field.
- Strong working knowledge of SQL and the ability to independently analyse large & complex datasets.
- Working proficiency in Python for analysis, automation or model development.
- Demonstrated experience delivering an AI or analytics solution that influenced a business decision, improved a process or enabled stakeholder self-service.
- Experience working with business metrics and processes with the corresponding analytics frameworks.
- Ability to build scalable analytical outputs rather than repeatedly solving the same problem.
- Familiarity with data platforms such as Tableau, Snowflake, Databricks or comparable tools.
- Prior exposure to machine-learning models including data preparation, feature engineering, model validation and performance evaluation is a plus.
- Exposure to fintech, SaaS, consumer technology or digital-product environments is a plus.
Responsibilities
- Partner with business and product teams to translate open-ended problems into clear analytical questions, measurable hypotheses and actionable recommendations.
- Analyse customer journeys, funnels, engagement, and retention to identify growth opportunities.
- Conduct root-cause analyses to explain changes in business metrics and recommend corrective actions.
- Design and evaluate experiments with appropriate statistical and business context.
- Develop dashboards, automated reporting and analytical pipelines that enable reliable decision-making.
- Build or contribute to AI-enabled analytics solutions or decision-making tools.
- Collaborate with data engineering teams to improve data definitions, analytical datasets, metric consistency and data quality.
- Present findings to business stakeholders with storytelling and ability to zoom-out appropriately.
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