Design, develop, and maintain interactive dashboards and reports using BI tools (e.g., Tableau, Power BI, Looker) to enable real-time visibility into key business metrics.
Extract, clean, transform, and model large, complex datasets from diverse sources using SQL, Python, and other data processing tools.
Apply statistical analysis and machine learning techniques to build predictive models for forecasting, customer segmentation, and operational optimization.
Collaborate with stakeholders across departments to understand business needs and translate them into data solutions and KPIs.
Automate data pipelines and workflows to improve data accuracy, reduce manual effort, and ensure timely delivery of insights.
Conduct A/B testing and experimental design to evaluate product changes and marketing initiatives.
Communicate findings clearly and effectively to technical and non-technical audiences through presentations, reports, and visual storytelling.
Stay current with emerging trends in data science, AI, and business intelligence to continuously enhance analytical capabilities.





Requirements
Bachelor’s or Master’s degree in Computer Science, Statistics, Mathematics, Data Science, or a related quantitative field.
2–5 years of experience in business intelligence, data analysis, or data science within a technology or data-intensive workplace.
Proficiency in SQL for complex data querying and manipulation.
Solid programming skills in Python (with libraries such as Pandas, NumPy, Scikit-learn) and/or R.
Hands-on experience with BI tools such as Tableau, Power BI, or Looker for dashboard development and data visualization.
Experience with data warehousing concepts and tools (e.g., Snowflake, Redshift, BigQuery).
Understanding of statistical modeling, hypothesis testing, and machine learning algorithms.
Excellent problem-solving skills, attention to detail, and ability to work independently and in agile teams.
Solid communication and storytelli

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