📧 Email: [email protected]
📞 Phone: +4915566226766
🌐 LinkedIn: linkedin.com/in/udithawick
Data Science and Business Analytics Professional with 15+ years of experience delivering AI-driven insights, predictive modeling, and scalable data solutions. Proven expertise in analytics strategy, machine learning, data pipeline engineering, and visualization tools. Adept at collaborating with stakeholders, mentoring professionals, and streamlining processes through automation and innovation.
- University: University of Europe for Applied Sciences, Berlin
- Thesis: "Weather Responsive AI for Real-time Battery Optimization in Electric Vehicles: A Case Study of German Urban Centers."
- Relevant Coursework: Machine Learning, Deep Learning, Statistical Modeling, Process Optimization, Data Analytics & EDA
- Completion Date: 2024
- Institution: ReDI School of Digital Integration, Berlin
- Completion Date: June 2024
- Institution: NVIDIA Corporation, USA
- University: University of Ruhuna, Sri Lanka
University of Europe for Applied Sciences – Berlin, Germany
October 2024 – Present
- Mentored 200+ students in Python, data analytics, machine learning, and AI model development.
- Delivered real-world projects, including fraud detection systems and predictive analytics models.
- Guided students in building data pipelines and deploying predictive models for business applications.
- Developed custom teaching materials emphasizing practical applications.
Al-Babtain Group of Companies – Kuwait
October 2022 – July 2023
- Built machine learning models, increasing predictive accuracy by 25%, including demand forecasting systems that reduced stockouts by 15%.
- Enhanced analytics systems with AI-driven insights and customer segmentation models, boosting ROI by 20%.
- Designed scalable data architectures using PostgreSQL, Python ETL pipelines, and Docker, enabling real-time data processing.
- Implemented live dashboards for real-time performance tracking and business decision-making.
Al-Mutawa Group of Companies – Kuwait
December 2007 – October 2022
- Led analytics projects, improving operational efficiency by 30% through data-driven insights.
- Delivered visualizations using Tableau and Power BI, enabling leadership to make informed decisions.
- Automated reporting workflows, saving 15+ hours per month and enhancing data accessibility.
- Implemented live dashboards to monitor performance metrics and optimize operations.
January 2010 – Present
- Developed machine learning models, including sentiment analysis tools, improving customer satisfaction by 10%.
- Built ETL pipelines with Python and SQL, enhancing data reliability and reducing manual processing by 20%.
- Created a recommendation engine, increasing cross-selling opportunities by 18%.
- Delivered insights through visualizations in Tableau and Power BI, empowering data-driven decisions.
- Programming Languages: Python, SQL, Go, MS .NET (VB.NET, ASP.NET)
- Machine Learning & AI: Predictive Modeling, NLP, Model Optimization, Neural Networks
- Data Engineering: ETL Processes, Data Pipelines, Docker, Cloud Technologies
- Visualization Tools: Tableau, Power BI, Matplotlib, Seaborn
- Database Management: PostgreSQL, MS SQL, MySQL
- Cloud Platforms: AWS EC2, Google Cloud
- Project Management: Agile (Scrum, Kanban), Jira, Trello, Notion
- Description: Built an AI-driven framework to optimize electric vehicle (EV) battery performance based on weather data.
- Technologies Used: Python, TensorFlow, Pandas, Matplotlib, Seaborn
- Description: Analyzed sentiments in tweets to detect patterns and trends.
- Technologies Used: Pysentimentio, Python, Pandas, Matplotlib, Seaborn
- Description: Developed an application to calculate ingredient costs and net profits based on POS and purchase data.
- Technologies Used: MS .NET, SQL, Power BI
- AWS Cloud Practitioner (2024)
- Microsoft Power BI Data Analyst (2023)
- Python for Data Science (Coursera)
- Languages: English (Fluent), German (A1 - Progressing)
- Location: Berlin, Germany
- Availability: Immediate
- Personal Projects: Developing cost-optimization tools for the gastronomy industry and predictive modeling for logistics operations.
UpdatedOn 8/1/2025 @Berlin