full-stack engineer · growth & paid media

Rakesh Singh I build the product and then buy the traffic that proves it works.

Python JavaScript React Google Ads Meta Ads GA4 · Attribution
live_signal.py — blended ROAS, last 30 days
0Blended ROAS
0CAC (₹)
0Conv. rate
0Years shipping & scaling
0Ad spend managed
0Products & landing systems
0Median CAC reduction

Selected work

Every project here has a shipping story and a number attached to it. Filter by the side of the problem you care about.

What I actually do all day

Two columns, one job: make the thing, then make the thing sell. The overlap — tracking, data pipelines, landing page speed — is where most of the gains hide.

Build

Python · Django, FastAPI, pandas92
JavaScript · React, Node, D388
CSS · design systems, animation84
SQL · Postgres, BigQuery80
AWS · Docker, CI/CD74

Grow

Google Ads · Search, PMax, Shopping90
Meta Ads · creative testing at scale86
Server-side tracking · GA4, CAPI85
CRO · experiment design82
Attribution & incrementality modelling78

How the two sides talk

A campaign is just a dataset with a budget attached. Here's the same pipeline in the three languages I reach for most.


    

Unit economics, in real time

Move the sliders the way a client does in a kickoff call. Everything recalculates on the spot, including the point where the campaign stops being profitable.

ROAS
Cost per acquisition
Orders / month
Gross profit after ads

Got a product that needs both halves?

Best fit: a team that has traction but can't tell which channel is causing it, or a build that needs to launch with tracking done properly from day one. Based in Delhi, working with teams across IST and EST hours.

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