Lead Data Scientist
NielsenIQ
Data Scientist – Geospatial Foundation Models
satsure· Dhaarini
About this role
About SatSure
SatSure is a deep tech, decision intelligence company working at the nexus of agriculture, infrastructure, and climate action — creating impact for the other millions, with a focus on the developing world. As part of this mission, we're building geospatial foundation models that learn directly from Earth observation data — optical, SAR, and elevation — at scale. This role sits at the heart of that effort: architecting and training large-scale models that can generalize across geographies, sensors, and time. You'll be shaping the core intelligence layer that powers insights for millions, not just fine-tuning someone else's model.
Role
In foundation model development, data is the moat. You will drive the transformation of petabytes of raw geospatial data into a high-quality, high-entropy training and evaluation corpus.
This role sits at the intersection of remote sensing, data engineering, and ML, ensuring that models learn from diverse, representative, and well-curated data at scale.
Key Responsibilities
Data Curation & Pre-training Datasets
- Design and implement data curation pipelines for large-scale pre-training datasets
- Develop sampling strategies to ensure:
- Geographic and biome diversity
- Coverage across seasons, sensors, and resolutions
- Mitigate dataset biases (e.g., over-representation of cloud-free or high-income regions)
- Balance trade-offs between data quality, diversity, and scale
Evaluation Frameworks (Earth-Bench)
- Design and own a comprehensive evaluation framework (“Earth-Bench”) to assess:
- Representation quality (post-SSL embeddings)
- Transfer performance on downstream tasks:
- Segmentation
- Yield prediction
- Disaster mapping
- Define metrics and benchmarks that reflect real-world generalization across geographies and time
- Continuously evolve evaluation as new datasets, sensors, and tasks emerge
Data Systems & Pipeline Thinking
- Build and maintain scalable data pipelines for ingestion, processing, versioning, and access
- Work with ML and platform teams to:
- Enable efficient data loading and training at scale
- Optimize storage formats and access patterns (e.g., chunking, caching)
- Ensure datasets are:
- Reproducible
- Well-documented
- Easily usable across teams
Data-Centric ML Thinking
- Analyze how data quality, diversity, and freshness impact model performance
- Partner with researchers to:
- Identify failure modes driven by data gaps
- Improve datasets to unlock model gains (not just model changes)
- Treat data as a first-class lever for improving model quality
Preferred Background
Domain Expertise
- 3–5 years of experience in Applied Data Science at scale
- Strong understanding of remote sensing fundamentals, including:
- Atmospheric correction
- SAR backscatter
- Orthorectification
- Familiarity with multi-sensor data (optical, SAR, DEM, etc.)
Data Engineering at Scale
- Experience working with large-scale (TB–PB) datasets across the ML lifecycle
- Hands-on experience with:
- Distributed data processing
- Efficient storage and retrieval strategies
- Understanding of how data pipelines interact with model training workflows
Tooling (Geo Stack)
- Experience with geospatial data tooling, such as:
- Xarray, Dask, Rasterio, Zarr
- Google Earth Engine (nice to have)
Mindset
- Strong data intuition—ability to reason about bias, coverage, and representativeness
- Systems thinking: understands how data decisions impact model behavior at scale
- Comfortable working in ambiguous, evolving problem spaces
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
Interview Process:
- Intro call
- Assessment
- Presentation
- Interview rounds (ideally up to 3-4 rounds)
- Culture Round / HR round
Frequently Asked Questions
Is the salary disclosed for the Data Scientist – Geospatial Foundation Models position at satsure?
The salary for this Data Scientist – Geospatial Foundation Models role at satsure is not publicly listed. Click "Apply Now" to learn more about the compensation package on their official careers page.
Where is the Data Scientist – Geospatial Foundation Models position at satsure located?
This Data Scientist – Geospatial Foundation Models role at satsure is based in Bangalore, India. The position is listed as on-site or hybrid. Check the full job description or apply directly to confirm the work arrangement.
Is the Data Scientist – Geospatial Foundation Models role at satsure full-time or part-time?
This is listed as a FULL TIME position. It is posted as a Data Scientist – Geospatial Foundation Models role in the Dhaarini department at satsure.
Which team or department does the Data Scientist – Geospatial Foundation Models at satsure belong to?
This Data Scientist – Geospatial Foundation Models position is part of the Dhaarini department at satsure. See the full job description for more information about the team structure and responsibilities.
How do I apply for the Data Scientist – Geospatial Foundation Models position at satsure?
Click the "Apply Now" button on this page. You will be redirected to satsure's official application portal hosted on keka where you can submit your application directly.
When was the Data Scientist – Geospatial Foundation Models job at satsure posted?
This Data Scientist – Geospatial Foundation Models position at satsure was posted on Jun 19, 2026. Apply as soon as possible — early applications are often reviewed first.
Data Scientist – Geospatial Foundation Models
satsure
You'll be redirected to satsure's official application page on keka.