π I'm a passionate Data Scientist with a deep love for uncovering insights from data and transforming complex datasets into actionable business strategies. With a strong foundation in statistics, machine learning, and programming, I specialize in building data-driven solutions that drive innovation and solve real-world problems.
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π Data Enthusiast: Experienced in working with large datasets, I have expertise in data cleaning, exploratory data analysis (EDA), and visualization to derive key insights.
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π€ Machine Learning Practitioner: Proficient in designing and implementing models such as regression, classification, clustering, and deep learning using tools like Python (pandas, NumPy, Scikit-learn, TensorFlow) and SQL.
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π Analytics Expert: Skilled in leveraging advanced statistical techniques to forecast trends, optimize processes, and guide decision-making through predictive analytics and A/B testing.
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π Real-World Problem Solver: With experience across domains like finance, e-commerce, and healthcare, I bring both technical and business acumen to create impactful solutions.
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π» Technical Skills: Python, R, SQL, TensorFlow, Scikit-learn, Tableau, Power BI, Docker, and Git.
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π― On a Mission: To push the boundaries of what data can achieve, while continuously improving my skills and learning cutting-edge techniques in AI, deep learning, and big data technologies.
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Transform raw data into actionable insights using predictive models, data analysis, and visualization techniques.
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Design and develop machine learning models to solve real-world challenges, from customer churn prediction to NLP-based sentiment analysis.
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Leverage my software engineering background to build scalable, efficient pipelines for data collection and processing.
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Passionate about big data and distributed systems, constantly exploring new technologies to process and analyze large datasets.
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Programming Languages: Python, R, SQL, JavaScript, HTML, CSS, JAVA, C, C++
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Machine Learning & AI: Scikit-learn, TensorFlow, Keras, NLP (Natural Language Processing)
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Data Tools: Pandas, NumPy, Tableau, Power BI
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Big Data Technologies: Apache Spark, PySpark
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Software Development: Spring Boot, Flask, RESTful APIs
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Cloud & DevOps: Microsoft Azure, CI/CD Pipelines, Git, Docker
- Customer Churn Prediction: Built a classification model for predicting telecom customer churn using Random Forest and Logistic Regression, helping the business reduce customer loss.
- Sentiment Analysis using NLP: Analyzed sentiment from social media posts using VADER and SpaCy, delivering actionable insights on customer satisfaction.
- ETL Pipeline Optimization: Designed and optimized an ETL pipeline that reduced processing time by 40%, enabling real-time data analysis.
π What I'm Exploring:
Currently diving into Natural Language Processing (NLP) and Large Language models to explore new ways of interacting with data.
I love collaborating on projects that push the boundaries of machine learning and data analytics. Feel free to reach out if youβre working on something exciting or if you'd just like to discuss new trends in data science and AI.
π« Contact Me:
- Email: [email protected]
- LinkedIn: Connect with me