|
|
🌐 (Portfolio)
About Me: ⬆️ Scroll to top
I'm Karthick Vel Kathirvel, a recent graudate of MS in Business Analytics at The University of Texas, Austin. With a tech toolkit powered by Python, SQL, Power BI, Azure and Databricks, I'm diving deep into data science and analytics to unearth insights that drive strategic business decisions.
- 🌱 I’m learning about sustainable supply chain optimizations through my capstone project with Celonis.
- 👯 I’m looking to collaborate on projects that fuse analytics with real-world business applications.
- 💬 Ask me about anything from data science to the best diving spots!
- 🔭 I’m currently working on a dynamic retail sales forecasting model using Apache Spark and Airflow.
- ⚡ Fun fact: I'm an avid debater and love exploring the complexities of evolutionary psychology.
- 🏆 Certifications: Microsoft Certified Data Analyst - Power BI, Udemy Certified in Spark and Python for Big Data with PySpark
 LeetCode SQL Top 50 Badge |
 LeetCode SQL Advanced 50 Badge |
 LeetCode 30 Days of Pandas Badge |
My Favorite Projects: ⬆️ Scroll to top
Deciding on an Electric Scooter - Visit the project here:
How can you determine the best electric scooter to purchase using detailed analysis of user feedback and expert reviews on Amazon and YouTube?
- What do you need to have? Identify three key features you want in a scooter.
- Solution: A list of the top three scooters with detailed pros and cons for each, tailored to your chosen features.
- Technologies Used: Python (Selenium, Pandas), GPT-4 (Large Language Model), Natural Language Processing.
Enhancing Metro Rail Operations - Visit the project here:
As an executive responsible for metro rail efficiency, how can you apply advanced predictive maintenance techniques to reduce service interruptions and improve reliability?
- What do you need to have?: Access to a day’s worth of sensor data from the trains.
- Solution: Predictions on whether a train is likely to experience a breakdown within the next day, enabling proactive maintenance.
- Technologies Used: Python, Autoencoders (Variational and Sparse).
Optimizing Financial Investments in the NASDAQ-100 - Visit the project here:
As an investor aiming to maximize returns, how can you employ sophisticated hybrid optimization techniques to accurately track the NASDAQ-100 index while ensuring cost-efficiency?
- What do you need to have?: Decide on the number of stocks you wish to invest in.
- Solution: A portfolio of stocks optimized to provide maximum returns, effectively emulating the NASDAQ-100 index.
- Technologies Used: Python (Pandas, Gurobi).
Skills: ⬆️ Scroll to top
| Skills | |
|---|---|
| Data Processing & Big Data |
|
| Programming Languages |
|
| Cloud Platforms |
|
| Machine Learning Frameworks |
|
| Visualization and Reporting Tools |
|
| Web Development and APIs |
|
| Database Technologies |
|
| Automation Tools |
|
| Miscellaneous |
|
Volunteering and Interests: ⬆️ Scroll to top
Volunteer at AustinPetsAlive!, providing care and optimizing operations. Interests include Debating, Horology, IoT, Evolutionary Psychology, Deep Sea Diving, and Tennis.
How to Reach Me: ⬆️ Scroll to top
Feel free to connect with me if you are interested in collaborating on projects or if you want to discuss any of the topics I'm passionate about!
- 📫 How to reach me: [email protected] or LinkedIn