As a multidisciplinary professional with expertise in data science, machine learning, engineering, and project execution, I offer a wide range of services tailored to enhance decision-making, optimize systems, and drive innovation across industries such as AI, mining, construction, and industrial automation.
Core Capabilities in Data Science & Machine Learning
- Data Analysis & Visualization: EDA, trend discovery, and actionable insights using Python (Pandas, NumPy, Matplotlib, Seaborn).
- Model Development: Supervised and unsupervised models (e.g., regression, classification, clustering, time series forecasting).
- ML Deployment: Streamlit, Flask APIs, model interpretability (SHAP, LIME), GitHub-ready pipelines.
- Predictive Maintenance & Anomaly Detection: Use ML/AI for industrial and infrastructure health monitoring.
Tools & Technologies
Languages: Python, SQL
Data & ML: Scikit-learn, TensorFlow, XGBoost, OpenCV, NLTK
Engineering Software: AutoCAD, Revit, STAAD.Pro
Dev & Deployment: GitHub, Streamlit, Docker, REST APIs
Project Tools: MS Excel (Advanced), Primavera P6, MS Project
Engineering & Technical Expertise
Civil, Mining Engineering and Structural analysis
Project Engineering, planning, procurement, budgeting, construction, and handover.
Research Engineering
Simulation Toolkits: Working with GMAT, SPICE
TRL-Based Development: Systems engineering approach for UAVs and airborne systems.
Research Writing & Prototyping: Documenting experimental plans, results, and design specifications at academic and industry levels.
Business & Strategy
Financial Planning & Analysis: Budget forecasting, cost-benefit evaluations, CAPEX/OPEX planning.
Production Efficiency Audits: Optimization of underground mining and construction workflows using data.
Cross-Functional Collaboration: Able to bridge technical, engineering, and management teams to deliver results.
Value to Employers
Versatility: Blend of engineering field experience with AI/ML technical depth.
System Thinking: Capable of designing, executing, and refining multi-domain solutions from idea to implementation.
Result-Oriented: Driven by KPIs, ROI, and project impact—not just technical output.
Leadership Potential: Experienced leading interdisciplinary teams, mentoring, and building scalable systems.