Data Scientist | PhD in Industrial Engineering | Forecasting, Time Series, Python, Business & Financial Analytics
Are you looking to make smarter decisions with your data? Whether you're running a business, optimizing KPIs, or forecasting future trends, I help you turn raw numbers into strategy.
I’m a data scientist with a PhD in Industrial Engineering, specializing in time series forecasting, business analytics, and machine learning. My academic research focused on developing deep learning models (ConvLSTM2D) to forecast multi-currency financial markets — and I now apply the same precision to real-world projects.
🔹 What I Can Do for You:
1) Predict future trends (sales, demand, or market movement)
2) Structure and clean raw datasets
3) Build dynamic dashboards (Excel or Tableau)
4) Automate analysis pipelines in Python
5) Deliver insights with documentation, code, and visual reports
I focus on clarity, accuracy, and usability — every project is tailored to your goals and decision-making needs.
🛠 Tools & Techniques:
Python (Pandas, NumPy, TensorFlow, Statsmodels)
Excel, Tableau, Minitab
ConvLSTM2D, Regression, ARIMA, Hybrid models
Random Forest, SHAP, Feature Ranking
Work Terms
Availability:
I am available 20–30 hours per week, including weekends if needed. I respond to all client messages within 12 hours and prioritize regular, transparent communication.
Communication:
I work through Guru’s message system — depending on client preference. I provide structured updates throughout the project to ensure alignment and clarity.
Delivery & Revisions:
All deliverables include clean, well-documented code, visualizations, or forecasts (as applicable), along with supporting explanations or guides. Up to 2 revision rounds are included for each milestone unless otherwise discussed.
Payment Terms:
a) Fixed-Price Projects: Milestone-based payment structure via SafePay
b) Hourly Projects: Weekly billing based on tracked time and prior estimation
Data Responsibility & Legal Compliance:
Clients are fully responsible for ensuring that all shared data:
1) Is free from copyright restrictions
2) Does not contain personally identifiable or sensitive information (e.g., medical, financial records)
3) Is legally usable for the scope of work
This includes any datasets related to demographic profiling, gender, religion, race, or national origin where legal or ethical concerns may apply. I reserve the right to decline or pause work on data or tasks that may violate laws, platform rules, or ethical standards.