SatSure is hiring a Data Scientist to build and deploy end-to-end ML/DL solutions for high-impact use cases across agriculture infrastructure and climate. Youll work on real-world data problems using Python SQL and deep learning frameworks like PyTorch or TensorFlow.
About Us:
SatSure is a deep tech decision Intelligence company that works primarily at the nexus of agriculture infrastructure and climate action creating an impact for the other millions focusing on the developing world. We want to make insights from earth observation data accessible to all.
Join us to be at the forefront of building a deep tech company from India that solves problems for the globe.
Roles & Responsibilities:
- Build and deploy ML/DL models (regression classification time-series CNNs transformers) to address high-impact business and operational problems.
- Drive the full data science lifecycle from problem scoping and data preparation to modeling validation (A/B tests back-tests) and production deployment.
- Develop modular interpretable pipelines using Python SQL and ML libraries (PyTorch TensorFlow scikit-learn) with a focus on scalability and reliability.
- Work with speed and agility to build quick POCs/MVPs in ambiguous or low-data environments balancing rigor with iteration.
- Translate business needs into intelligent systems embedding models into decision workflows and communicating results to influence cross-functional decisions.
Qualifications:
- 3 - 5 years of hands-on experience building and deploying ML and DL models (classification regression time-series clustering CNNs transformers etc.) in real-world settings.
Must-Have Skills:
- Built end-to-end ML/DL workflows from data ingestion and preprocessing to training evaluation and deployment.
- Proficient in Python (pandas numpy xarray scikit-learn PyTorch/TensorFlow) and SQL for scalable ML pipelines.
- Strong foundation in ML theory deep learning (CNNs transformers) and statistical modeling (A/B testing causal inference).
- Experienced in handling diverse data types with robust preprocessing feature engineering and transformation pipelines.
- Skilled in aligning ML solutions with business goals building fast POCs and communicating results for cross-functional impact.
Good to Have:
- Familiar with PostgreSQL geospatial libraries (geopandas rasterio) and data visualization tools (Tableau Power BI matplotlib seaborn).
- Understanding of MLOps deployment practices and software development workflows including version control and agile delivery.
- Exposure to emerging Agentic AI concepts such as tool-using agents RAG pipelines and feedback loops.
Benefits:
- Medical Health Cover for you and your family including unlimited online doctor consultations
- Access to mental health experts for you and your family
- Dedicated allowances for learning and skill development
- Comprehensive leave policy with casual leaves paid leaves marriage leaves and bereavement leaves
- Twice a year appraisal
Interview Process:
- Intro call
- Assessment
- Presentation
- Interview rounds (ideally up to 3-4 rounds)
- Culture Round / HR round