Welcome to my GitHub profile! I'm a data science professional with 3 years of experience in the Data Science domain, skilled in developing interactive dashboards, building dynamic reports, analyzing large-scale datasets, and collaborating with cross-functional teams to drive data-driven decision-making.
- I'm exploring Data Analytics Applications in different industries such as Finance, Marketing, and Retail.
- I am working on building End-to-End Production Level Dashboard from Extract Transform Load (ETL) data from different sources to an interactive dashboard.
- Also, I'm building an integrated dynamic HR Analytics Dashboard to visualize and analyze key HR metrics, such as employee attrition, performance, and diversity.
- I'm expanding my Data Analysis knowledge and exploring advanced Big Data architectures using PySpark, Hive, Snowflakes, and many more to enhance the accuracy and quality of my Data Analyst projects.
- I'm also diving deeper into recommendation systems, exploring different algorithms and strategies to improve the precision and personalization of product recommendations.
- Supply Chain Analytics: https://github.com/abbas99-hub/Supply-Chain-Analytics
- Job Recommendation System: https://github.com/abbas99-hub/Job-Recommendation-System
- Predict HR Employee Joining using ML: https://github.com/abbas99-hub/Predict-HR-Employee-Joining-Company-Using-ML
- HR Job Salary Analytics Dashboard: https://app.powerbi.com/links/J5PBneu_XH?ctid=80422497-e632-410a-964a-2cee17aa1964&pbi_source=linkShare
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Data Analyst at Litmusblox: 8/2020-6/2022
- Developed and implemented a Job Recommendation System that increased candidate-job matching accuracy by 30%.
- Conducted A/B tests on different product features processes, resulting in a 12% increase in conversion rate.
- Presented insights from website clickstream data, resulting in a 30% improvement in decision-making..
- Developed a predictive model that accurately identified potential churn cases with an 85% accuracy rate .
- Identified critical company KPIs for revenue, customer acquisition, and customer satisfaction.
- Enhanced user insights, contributing to a 10% increase in personalized user experiences .
- Created pivot tables and charts to visualize KPIs, resulting in a reduction of manual reporting effort by 40%
- Tools used: AB Testing, Power Query, SQL, MS Excel, Clustering, Scikit-Learn, Machine Learning, TensorFlow.
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Data Analyst at Peopleblox: 6/2022-6/2023
- Built and maintained data pipelines to extract, transform, and load data from various data sources like databases, spreadsheets, and APIs using Databricks, Google Cloud.
- Extracted insights from website clickstream data, resulting in a 30% improvement in decision-making.
- Delivered an A/B Testing tool to test the impact of different training programs on employee skills acquisition, job performance, and satisfaction. Techniques used: Hypothesis Testing, T-Test, Chi-Square Test, P-Value, Normal Distribution.
- Presented findings to optimize the website user experience and increased conversion rate by 15%, by creating an interactive dashboard.
- Performed cohort analysis for customer retention, which resulted in 40% of customers from Q1 remaining active after nine months.
- Tools used: Python, SQL, PowerBI, VBA, Data Modeling, Descriptive Statistics, Alteryx, and MS Excel.
- Check out my latest articles on Medium where I share insights and tutorials related to HR analytics, data science, and machine learning.
- LinkedIn: https://www.linkedin.com/in/abbas-behrainwala-1b669b183
- Medium: https://medium.com/@abbasbehrain95
- I'm always interested in connecting with professionals and researchers in the field of data science and machine learning.
- Feel free to reach out if you have any questions, project ideas, or opportunities for collaboration!