01 · about
Curious by default, technical on purpose.
I'm Shreya, a statistics graduate who spent three years making financial data behave and is now in Amsterdam adding machine learning on top. I like figuring things out properly, and I care about whether the end result is actually useful to a real person.
the path so far
Statistics, properly
BSc (Hons) Statistics at Kirori Mal College, University of Delhi, finished with a CGPA of 8.12/10. The statistical modelling foundation everything else sits on.
Three years of messy data
As a Data Analytics Engineer at Galytix I built the ETL pipelines that turned scanned PDFs and inconsistent financial reports into analyst-ready datasets for Société Générale, covering 1,200+ global companies. I also led a team of 10 interns and trained new ones on the tooling.
Adding the ML layer
MSc Business Analytics at VU Amsterdam, on the Computational Intelligence track: machine learning, deep learning, NLP, stochastic modelling and optimisation. So far that has meant learning-to-rank on Expedia search logs and a recommender for Amsterdam tourist flows.
Next up
A six-month graduation internship from February 2027, the final part of the MSc.
how i work
A few things that stay true across projects.
- (01)
The why behind the what
A solution is much more satisfying when I understand why it works. I'd rather genuinely get it than memorise the right-sounding paragraph.
- (02)
Correct is not the same as good
"It works" and "it's good" are different bars. Wording, structure, edge cases and small inconsistencies all matter to me.
- (03)
Practical over clever
I like ideas that survive contact with the real world. A clever answer nobody can use is less interesting than one that actually moves a project forward.
- (04)
Iteration is the fun part
Getting from "okay" to "actually good" is where most of the craft lives, so I am not precious about first drafts.
- (05)
Find the weird thing
"This should be straightforward, but something about it is weird." That kind of detective work, in code or data, is my favourite kind of problem.
- (06)
Clear, not stiff
Output should make sense to humans, not just machines. Professional does not have to mean soulless.
When I'm not in a notebook.
- cooking
- Very into it, and always open to recipe recommendations.
- training
- Part of the routine, heavy lifting included.
- music
- Fred again.. is my favourite artist, no contest. The voice notes and date stamps on this site are a small nod.
- tools
- I'll research which free dictation app works best across every device so you don't have to. (Verdict: Aiko.)
- languages
- English (professional) · Hindi (native) · Dutch (learning)