MOHAMMED AASMAA

Entry-level ESG & Climate Analyst with a strong quantitative and analytical background from IIT Dharwad. Skilled in data analysis, modelling, and structured problem-solving with hands-on experience in Python, databases, and large-scale data systems. Strong interest in climate risk, decarbonisation, and sustainability analytics, with the ability to translate complex data into insights for reporting and decision-making.

Climate Risk & Financed Emissions Simulation Model 

• Developed a Python-based model to simulate company emissions and calculate financed emissions using PCAF-inspired methodology.
• Generated synthetic ESG datasets and performed portfolio-level carbon footprint analysis.
• Designed climate risk scoring logic and visualized sector-wise transition risk trends.
• Built analytics workflows for emissions reporting and decision-support insights.

Technologies: Python, Pandas, NumPy, Matplotlib, Data Analytics

Carbon Footprint Tracker & Analytics Tool

• Built a Python-based tool to calculate carbon emissions from energy use, travel, and consumption activities.
• Implemented emissions calculation logic using standard emission factors and generated category-wise analytics.
• Developed visualizations to analyse carbon footprint trends and identify key emission drivers.
• Provided automated insights for emission reduction and sustainability awareness.

Technologies: Python, Matplotlib, Data Analytics, CSV/SQLite

College Attendance Portal with Biometric Integration

• Built a scalable data-driven system supporting 2,000+ students, ensuring data accuracy and integrity.
• Designed optimized MySQL schemas for structured storage and reporting.
• Developed backend APIs for data ingestion and synchronization under unreliable network conditions.
  Technologies: Node.js, MySQL, JavaScript, ESP32

Full-Stack MERN E-Commerce Application

• Developed a data-intensive platform with structured user, product, and transaction datasets.
• Implemented REST APIs and MongoDB data models for scalable analytics-ready storage.
  Technologies: React.js, Node.js, MongoDB

Mesh Networking for Environmental Sensor Data (NRF52833)

• Designed low-power sensor data transmission architecture for environmental monitoring use cases.
• Focused on reliable data collection, system robustness, and real-time analytics readiness.
  Technologies: Embedded C, NRF52833, Environmental Sensors

Job Portal Backend (MVC Architecture) 

• Developed a Python-based model to simulate company emissions and calculate financed emissions using PCAF-inspired methodology.
• Generated synthetic ESG datasets and performed portfolio-level carbon footprint analysis.
• Designed climate risk scoring logic and visualized sector-wise transition risk trends.
• Built analytics workflows for emissions reporting and decision-support insights.

Technologies: Python, Pandas, NumPy, Matplotlib, Data Analytics 

Job Portal Backend (MVC Architecture)

• Built structured data pipelines for job and applicant datasets with authentication and role-based access.
• Implemented CRUD APIs, validations, and reporting-ready data structures.
  Technologies: Node.js, Express.js, MySQL

• Participated in Finance & Analytics Club activities and data analytics workshops.
• Mentored junior students in coding and analytical problem-solving.
• Attended seminars and workshops on sustainability, renewable energy, and climate change topics.
• Engaged in self-learning on ESG frameworks, climate risk, and sustainability analytics.

• Strong analytical and quantitative reasoning skills
• Detail-oriented with high ownership mindset
• Comfortable with ambiguity and multi-tasking
• Continuous learner with interest in ESG, sustainability, and climate risk analytics