Bangalore, India · Available for opportunities

Martiena.

A Python developer with a finance brain, building toward AI — one model, one pipeline, one decision at a time.

Two disciplines, one mind.

An engineer who reads balance sheets and trains models with equal interest.

Started in accounting and finance, moved into Python development at Elmeasure India, and now leaning hard into AI — building data analysis tools, automation, and the beginnings of ML-driven decision systems.

The MBA isn't a footnote. It's how I read systems before I write code for them.

  • Now Associate at Elmeasure India Pvt Ltd
  • Based in Bangalore, India
  • Focus Python · Data Analysis · AI / ML
  • Experience 4+ years in software engineering
  • Open to Full-time roles · Remote / Hybrid

Where I've built things.

Associate — Software

Jan 2022 — Present

Elmeasure India Pvt Ltd · Bangalore, India · Full-time

  • Designed and built Python tools for data analysis across internal product workflows, turning ad-hoc spreadsheet processes into repeatable scripts.
  • Wrote automation that cut manual reporting time substantially — moving the team from hours of Excel work to minutes of `python run.py`.
  • Currently exploring AI/ML applications for the company's data — early experiments with scikit-learn pipelines and forecasting models.
  • Translate between business stakeholders and engineering — the MBA finance background means I can hear "we need to know X" and turn it into a data model.

The toolkit.

Things I reach for daily, and things I'm sharpening for the AI direction I'm heading in.

→ Core
Python Data Analysis pandas NumPy SQL Git
→ AI / ML (Growing)
scikit-learn Jupyter Matplotlib Statistics LLM APIs
→ Adjacent
REST APIs Linux Excel / Sheets Financial Modeling Stakeholder Comms

Where I learned to think.

Master of Business Administration

Accounting & Finance · Kasireddy Narayanreddy College of Engineering and Research

2016 — 2019

Selected work.

PROJECT / 01

Reporting Pipeline Automation

Replaced a weekly manual spreadsheet routine with a Python pipeline that ingests raw data, validates it, generates summary reports, and emails them out — turning 6 hours of work into a scheduled job.

PythonpandasSQLcron
// Replace with real project
PROJECT / 02

Forecasting Experiments

Early-stage ML work using scikit-learn for time-series forecasting on internal metrics — baseline regression and tree-based models, with proper train/test splits and feature engineering from raw operational data.

scikit-learnNumPyJupyterMatplotlib
// Replace with real project

Let's talk.