Experience 🧑‍💻

ICF, Bangalore, India.

Automating manual tasks within the team using Python programming, increasing efficiency and productivity.
Developing intuitive and informative ArcGIS dashboards, Interactive web maps and creating online layers (vector and raster) to visualize and analyze energy data, facilitating decision-making for clients.
Conducting in-depth GIS analysis using ArcGIS Pro, Qgis and Python to identify trends, patterns, and spatial relationships within energy datasets, enabling data-driven insights.
Mapping transmission lines and substations using GIS analysis, providing accurate spatial representation of energy infrastructure.
Utilizing advanced features of Microsoft Excel for data analysis, manipulation, and quality assurance/quality control (QA/QC) of energy analysts' outputs.
Working extensively with US and Canada energy markets such as ERCOT, SPP, NYISO, ISONE, MISO, and WECC.etc, and familiarity with Energy Analyst tools such as TARA viewer, PowerGEN, PROMOD, TARA studio software, power flow cases, and velocity suite tool.
Managing large spatial datasets efficiently and integrating AI & ML analytical capabilities in order to provide innovative solutions to energy-related problems
Expertise in SQL, databases, and Azure cloud tools.
Technologies used: Python, ESRI dashboard, Web Maps, ArcGIS Pro, Energy Analysis tools.

Website: ICF

Automating of Remote Sensing & GIS tasks using python.
Water body monitoring, Oil Spill detection, Flood Mapping, Agricultural crop health monitoring through indices and Extraction of Time series data using GEE.
Worked with NOAA Oceanographic datasets such as SST, Chlor, Wind data and Finding of fishery locations.
LULC using ML and Traditional methods. Change detection Analysis using Idrisi.
Familiar with Raster datasets such as Sentinel 2, Sentinel 1 (SAR data), MODIS Aqua/Terra, Sentinel 3, DEM, Night light data, NOAA SST, MODIS NDVI & EVI, AETI (Evapotranspiration) , Precipitation.
Familiar with Geo Python Libraries: Geopandas, Rasterio, Shapely, scikit learn, xarrays, dask, rioxarray, gdal, fiona, numpy, pandas, matplotlib, postgresql.

Extracted building schema and objects details from IFC file using ifcOpneshell python.
Created Data Visualization and KPI in PowerBI & Teableau.
Created Data Pipeline from Database to PowerBI.
Worked in RESTAPI creation and connected them with BI tools.
Experienced in Agile (Scrum) way of working.
Technologies used: Python, PowerBI, Tableau, PostgreSQL, BIM data, IfcOpenShell.

Collaborate with the Location Intelligence team to deliver meaningful metrics, derive spatial trends, key insights, and analysis in clear, concise stories for various stakeholders at all levels
Compiles, analyzes, formats, and updates data gathered from various sources, using established processes and computational tools to create and/or maintain assets
Work on the large spatial and non-spatial dataset
Consult with the Leadership team to create data insights into the key business questions
As a member of the team, collaborate and process to work across a variety of data sources and technologies, such as GIS, SQL, BigQuery, Google Cloud, Google data studio,Tableau and Looker.
Use of Web GIS technologies to represent the Insights
Extract valuable insights from large, complex spatial and non-spatial data sets using Python/R, GIS tools and techniques
Monitor Key data elements across systems for accuracy and completeness. Proactively address data quality issues through direct engagement within the data providers and clients to identify root causes and develop strategies for continuous improvements in system data quality.
Serve as a subject matter expert for Geospatial data, reporting, and analytics
Provide recommendations for process automation and efficiency enhancements.
Technologies used: Python, Tableau, Google Data Studio, Looker, BigData, BigQuery.

Water body Monitoring, Forest vegetation Monitoring and ML classification using Google Earth Engine.
Geocoding using Here Maps API and Google Maps API - Python.
BigData Handling.
Development and Testing of WebGIS applications.
Technologies used: Nodejs, Reactjs, PHP, JavaScript, PostgreSQL, Qgis, Google Earth Engine.

Digital Soil Mapping of Rasipuram block, Salem District , Tamil Nadu.

Predicted basic soil properties such as sand, clay, silt, PH and OC using Quantile Regression Forest (Machine Learning ) algorithm in R Studio
Technologies used: R programming, SAGA gis, Qgis.