Data Analyst with around 3 years of experience excelling in optimizing data processes, data Modelling, Machine learning algorithms, Statistics. Specializes in crafting efficient MySQL queries and designing Tableau dashbo…
Data Analyst with around 3 years of experience excelling in optimizing data processes, data Modelling, Machine learning algorithms, Statistics. Specializes in crafting efficient MySQL queries and designing Tableau dashboards for streamlined reporting. A collaborative team player, adept at fostering data-driven decision-making. Utilizes big data tools for cost-effective processing and analysis, enhancing project efficiency. developed Tableau dashboards, optimizing marketing campaigns. Proficient in MySQL database design and A/B testing for performance optimization. Skillfully manages data storage and processing with measurable success, achieving a 15% improvement in reporting efficiency and a 20% reduction in data retrieval time.
Conducted exploratory data analysis (EDA) using Python libraries such as Pandas, Seaborn, and Matplotlib to uncover hidden patterns and anomalies in large datasets.
Implemented A/B testing methodologies for marketing campaigns, utilizing statistical analysis tools and Azure services for hypothesis testing and performance optimization.
Utilized Azure Databricks for big data analytics, leveraging Apache Spark for scalable and efficient data processing.
Applied advanced statistical techniques, including regression analysis and classification models, using Scikit-learn for predictive modeling.
Designed and developed data visualization solutions using Plotly Dash for interactive and real-time visualizations.
Conducted sentiment analysis on customer feedback using natural language processing (NLP) techniques with spaCy and Azure Cognitive Services.
Led a cross-functional team in the implementation of a customer segmentation project, utilizing unsupervised learning techniques with Azure Machine Learning.
Introduced data storytelling techniques, creating compelling narratives around key performance indicators (KPIs) for executive presentations using Microsoft Power BI.
Implemented a comprehensive data cataloging system using Azure Purview, enhancing metadata management and improving data discoverability.
Conducted exploratory data analysis (EDA) using Python libraries such as Pandas, Seaborn, and Matplotlib to uncover hidden patterns and anomalies
in large datasets.
Implemented A/B testing methodologies for marketing campaigns, utilizing statistical analysis tools and Azure services for hypothesis testing and
performance optimization.
Utilized Azure Databricks for big data analytics, leveraging Apache Spark for scalable and efficient data processing.
Applied advanced statistical techniques, including regression analysis and classification models, using Scikit-learn for predictive modeling.
Designed and developed data visualization solutions using Plotly Dash for interactive and real-time visualizations.
Conducted sentiment analysis on customer feedback using natural language processing (NLP) techniques with spaCy and Azure Cognitive Services.
Led a cross-functionalteam in the implementation of a customer segmentation project, utilizing unsupervised learning techniques with Azure Machine
Learning.
Introduced data storytelling techniques, creating compelling narratives around key performance indicators (KPIs) for executive presentations using
Microsoft Power BI.
Implemented a comprehensive data cataloging system using Azure Purview, enhancing metadata management and improving data discoverability
Designed and engineered dynamic reporting dashboards using Tableau and Power BI for nuanced insights into customer behavior and campaign performance.
Spearhead the implementation of advanced SQL queries to fine-tune database management, ensuring accelerated data retrieval.
Lead the development of ETL pipelines using AWS Glue and Apache Spark, streamlining data integration and processing with cost-effective solutions.
Drive innovative machine learning initiatives, employing TensorFlow for deep learning models, resulting in a 25% improvement in predictive accuracy.
Collaborate seamlessly within cross-functional teams, implementing Agile methodologies for agile project execution.
Utilize advanced Python libraries such as Scrapy for web scraping, expanding data sources and enriching analysis.
Develop and maintain automated data pipelines using Apache Airflow, ensuring efficient and scheduled data processing.
Implement data encryption measures with the cybersecurity team.
Utilize natural language processing (NLP) techniques with spaCy for sentiment analysis on customer feedback, enhancing marketing strategies.
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