Job Summary

We are seeking a detail-oriented and results-driven Data Analyst with 3–5 years of professional experience. In this role, you'll be responsible for transforming complex data into actionable insights that support strategic decision-making across the organization.

Key Responsibilities

Analyze large datasets to identify trends, patterns, and actionable insights that drive business performance - with a primary focus on subscription-related metrics (e.g., acquisitions, resurrections, churn, revenues, MRR, ARPU, LTV) and user engagement (e.g., content streaming behavior, session frequency, retention)
Perform cross-analysis, user segmentation, and classification to identify behavioral patterns, target cohorts, and optimize user lifecycle strategies (e.g., acquisition channels, churn risk, high-LTV segments) ; Leverage segmentation and classification techniques to group users by behavior, value, and lifecycle stage, enabling more targeted marketing, retention, and content strategies
.Build dashboards, reports, and visualizations (such as Tableau, Power BI, or Looker)
.Work closely with cross-functional teams (Product, Marketing, Finance, etc.) to define data needs and deliver analytical solutions
.Translate business questions into analytical problems and provide recommendations based on data
.Perform data validation, cleaning, and transformation (ETL/ELT flows) to ensure data accuracy and integrity
.Assist in designing and implementing data collection processes and best practices
.Communicate findings clearly and concisely to both technical and non-technical stakeholders

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Qualifications

Bachelor's degree in Data Science, Statistics, Mathematics, Computer Science, Economics, or a related field
3–5 years of experience in a data analyst or business intelligence role
highly proficient in SQL and working with relational databases (AWS Redshift, MySQL)
Proficiency in scripting language, mainly Python and PySpark
.Experience with data visualization tools (e.g., Tableau, Power BI, and ideally Looker
Strong analytical thinking and problem-solving skills
Solid understanding of statistical methods and data modeling techniques, including dimensional modeling (e.g., star and snowflake schemas) and third normal form (3NF) entity-relationship (ER) modeling
Proficiency in Excel
Excellent communication and presentation skills
Experience working with cloud-based data platforms (AWS : S3, Redshift
Exposure to tools like Airflow, or other data engineering workflows.

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