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Data

Hire senior data scientists from Bangladesh.

Analytics, BI, modeling, and ML for production. Our data scientists write SQL that scales, dashboards people actually use, and models that survive production drift.

Capabilities

What our Data engineers do.

  • Analytics + BI

    SQL-first warehouses (Snowflake, BigQuery), dbt models, semantic layers. Looker or Metabase that doesn't rot.

  • Modeling

    Forecasting, classification, recommendation. Boring, validated approaches before fancy ones.

  • Experimentation

    A/B platforms, sequential testing, CUPED variance reduction. Stats you can defend in a review.

  • MLOps adjacency

    Hand off to AI engineers cleanly. Feature stores, model registries, drift monitoring.

Default stackPythonSQLdbtSnowflakeBigQueryMetabase· We adapt to your stack — these are starting points, not constraints.

How fast

Hire in 7–10 days.

From brief to first commit. We move when you move.

  1. 01

    Day 1–2

    Brief us. We shortlist 2–3 vetted candidates against your stack and seniority bar.

  2. 02

    Day 3–5

    Interview the shortlist. Pair on a real problem from your codebase if you want.

  3. 03

    Day 6–7

    Pick. We handle paperwork, NDA, equipment, and access.

  4. 04

    Day 8–10

    Ship. Your new engineer commits in their first week, not their first month.

FAQ

Common questions.

Do they ship to production?
Yes. We don't do dashboards-only or notebook-only data scientists.
How is this different from AI engineering?
Different end of the same pipeline. Data scientists own discovery + measurement; AI engineers own serving + scale.

More roles

Other engineers we place.