Data Scientist

Job Title: Data Scientist – Forest Analytics & Environmental Intelligence

Job Summary

We are seeking a passionate and skilled Data Scientist to work at the intersection of data science and environmental sustainability, focusing on forestry, ecosystem monitoring, and geospatial intelligence. You will develop and validate machine learning models, process large-scale geospatial and ecological datasets, and provide predictive insights to support forest management, biodiversity conservation, and carbon monitoring.

Key Responsibilities

l Implement and validate predictive and prescriptive models for forest health, land use change, biomass estimation, and biodiversity risk.

l Design and maintain statistical and machine learning models, leveraging big data sources such as remote sensing imagery, LiDAR, and IoT sensor data.

l Write efficient and reusable programs for cleansing, integrating, and analyzing structured and unstructured geospatial data.

l Collaborate in an Agile, interdisciplinary environment with data scientists, ecologists, software engineers, and policy stakeholders.

l Communicate technical findings to both technical and non-technical stakeholders, including government bodies, environmental agencies, and NGOs.

l Work with cloud platforms and AI frameworks to build scalable and production-ready models for environmental decision-making.

l Develop proof-of-concepts (POCs) showcasing the power of generative AI and automation in forestry and conservation scenarios.

l Document design decisions, modeling results, and best practices through white papers and internal technical documentation.

Required Qualifications

l Bachelor’s Degree in Computer Science, Environmental Engineering, Forestry, Data Science, or a related field.

l Preferred Qualifications

l Master’s Degree in Data Science, Remote Sensing, Environmental Informatics, or related discipline.

l Technical & Professional Expertise

l Strong programming skills in Python, with experience in PySpark for large-scale data processing.

l Proficiency with AI/ML libraries like Scikit-learn, TensorFlow, PyTorch, Keras, and Hugging Face.

l Experience with geospatial data tools such as GeoPandas, rasterio, GDAL, xarray, and visualization libraries like Matplotlib, Folium, or Plotly.

l Ability to develop end-to-end ML pipelines, from data wrangling to deployment.

l Familiarity with cloud services (AWS, GCP, or Azure) and tools like Google Earth Engine or Sentinel Hub.

l Understanding of remote sensing, NDVI/EVI indices, and forest cover change detection.

l Ability to evaluate model results, assess performance, and clearly communicate insights to diverse audiences.

Preferred Experience

l Experience with forestry, agriculture, sustainability, or natural resource monitoring projects.

l Background in working with satellite or drone imagery, climate datasets, or spatio-temporal models.

l Demonstrated ability to translate research and models into actionable field-ready tools.

Job Type: Full-time

Pay: ₹1,200,000.00 - ₹1,500,000.00 per year

Benefits:

• Provident Fund

Work Location: In person