Highly analytical Data Analyst with hands-on experience at Sun Pharmaceutical Industries Ltd., specializing in leveraging advanced statistical modeling, machine learning, and big data analytics to transform complex datasets into actionable business intelligence. Proficient in Python, R, Hadoop, PySpark, Tableau, and Power BI, I excel at developing predictive models, creating dynamic dashboards, and optimizing data processes to drive significant improvements in decision-making and operational efficiency.
Data Analyst Intern
Ujjain, MP, India
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Summary
As a Data Analyst Intern at Sun Pharmaceutical Industries Ltd., I spearheaded data analysis initiatives across HR and customer insights, leveraging statistical modeling and visualization tools to drive data-driven decision-making.
Highlights
Developed and deployed a predictive model to benchmark employee performance ratings, leveraging key attributes to enhance appraisal fairness and consistency across diverse employee groups.
Designed and implemented real-time, interactive dashboards using Tableau and Power BI, enabling stakeholders to monitor critical KPIs and gain immediate insights for data-driven decision-making.
Integrated and harmonized complex datasets from disparate sources including ERP, clinical trial systems, sales platforms, and HRMS, establishing a comprehensive and unified data foundation for analytical initiatives.
Executed comprehensive data cleansing, validation, and preprocessing on large structured and unstructured datasets, significantly improving data quality and integrity for downstream analysis and reporting.
Streamlined data management workflows by developing and implementing monthly/quarterly goal reports and robust QC procedures, enhancing reporting accuracy and operational efficiency for critical business functions.
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Master of Science
Big Data Analytics
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Bachelor of Science
Statistics
SQL, Python, R, Scala.
Hadoop, PySpark.
Tableau, Power BI.
Statistical Modeling & Analysis, Time Series Analysis, Hypothesis Testing, ETL Tools.
Machine Learning (ML), Deep Learning (DL).
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Summary
Analyzed historical population data and forecasted key vital statistics such as birth rate, death rate, and overall population growth, providing policy-relevant insights.
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Summary
Conducted in-depth analysis of employee performance ratings to identify patterns, bias indicators, and gaps in appraisal consistency across departments.
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Summary
Analyzed telecom customer data to detect churn patterns using logistic regression and decision tree models.