Website:
sling-shot.in
Job details:
Slingshot Analytics | Hyderabad/Bangalore (Hybrid) | 3–6 Months | Paid
A little about us
At Slingshot Analytics, we sit at a strange and exciting crossroads — where maps meet data, and data meets decisions. We work with complex geographic and demographic information and turn it into tools that actually help people make better calls. We move fast, we think carefully, and we care a lot about the quality of what we build.
Right now, we are quietly building something new. It is early-stage, it is ambitious, and we are not talking about it publicly yet. That is where you come in.
What this role is about
We need someone who genuinely likes working with spatial data — not just someone who has used QGIS once in a college project. This internship is about rolling up your sleeves and getting into the real, often messy work of building a geospatial product from scratch.
You will be working on the data side of a live, stealth-mode application. Think boundary data, demographic layers, spatial validation, and making sure everything is clean and structured enough to power an interactive map-based tool. You will be part of a small team, which means your work will actually matter and be visible — not buried in a queue somewhere.
Because the project is confidential, we will ask you to sign a Non-Disclosure Agreement before we walk you through the full picture. We know that asks for some trust upfront, and we take that responsibility seriously.
What your days will look like
- Cleaning up and validating spatial datasets — shapefiles, GeoJSON files, boundary tables, GeoPackages — the kind of files that never arrive perfectly formatted
- Joining geographic boundary data with demographic and administrative tables, and making sure the joins actually make sense
- Checking maps for geographic errors — gaps, overlaps, invalid polygons, mismatched projections — the details that break things if you miss them
- Supporting boundary analysis, unit aggregation, and spatial hierarchy work
- Running exploratory analysis on population and administrative data, and pulling out what is useful
- Writing clear, honest documentation about what the data is, how it was transformed, and what assumptions were made
- Testing how data layers behave inside the product — working closely with the engineering team during demo builds
- Creating QA notes, summary sheets, and clean exports that the team can actually use in presentations
What you should bring
You do not need to be an expert. But you should be genuinely comfortable with:
- QGIS or ArcGIS — not just the basics, but enough to do real spatial analysis
- Working with shapefiles, GeoJSON, and CSVs without needing a tutorial every time
- Understanding what coordinate systems and spatial joins actually do, not just how to click through them
- Excel or Google Sheets for structured data cleaning and QA
- Catching data problems — inconsistencies, missing values, broken geometry — before they become someone else's problem
- Writing documentation that a teammate can read and actually follow
- Working independently when things are ambiguous, which they sometimes will be
- Treating confidential data like it is confidential
If you also know Python — GeoPandas, Shapely, Pandas, Fiona — that is a real bonus. Same goes for PostgreSQL, PostGIS, or experience with census and administrative datasets. Even better if you have a genuine interest in how data shapes governance, public policy, or spatial planning.
What you will walk away with
This is not a role where you shadow someone and watch. You will be building something real, with a small team that actually values what you contribute. By the end of it, you will have:
- Hands-on experience building a geospatial product from the ground up
- A solid portfolio of applied spatial analysis work
- Mentorship from people who work at the intersection of data, geography, and real-world decision systems
- The experience of being part of a confidential, high-stakes build — which is genuinely rare for an internship
- A real shot at a full-time role if you do well
Stipend
Paid. Competitive based on your skill level. We will talk numbers early in the process — no surprises.
Click on Apply to know more.