Data Science Internship (Work From Home) at Firgun Labs
Firgun Labs is hiring a Data Science Intern for its product Nool, with the internship offered as a work from home opportunity and required field visits for sensor calibration and ground-truth collection. The role is centered on building the core algorithms that turn raw sensor signals into reliable production counts for textile and garment MSMEs. The internship is the primary 3-month option, with a monthly stipend of Rs. 25,000 – 35,000, and there is 1 opening. Applications are open on Internshala until 21 August 2026, and the internship can start immediately for candidates available between 22 July 2026 and 26 August 2026.
Standout fact: Nool places IoT sensors on sewing machines in textile and garment MSMEs, turning every stitch into a data point and building a financial stack on top of live production output.
About Firgun Labs and the Nool Product
Firgun Labs is an industrial-automation and financial-technology startup based in Bengaluru. Its broader mission is to build access to technology and finance for India’s MSMEs, especially the country’s approximately 75 million MSMEs. Within that mission, the product Nool focuses on textile and apparel MSMEs by using IoT sensors on sewing machines. The idea is to convert live production activity into verifiable data that can support working capital and machinery financing for nano job-work units.
Nool is described as building both the data infrastructure and the financial infrastructure on top of production output. That means the internship is not only about data science in the abstract, but about creating algorithms that can support a real operational and financial use case. The intern will work on the core logic that converts raw sensor signals into daily garment counts, helping make production measurable in a way that can be used downstream. This makes the role closely tied to industrial automation, time-series analysis, and practical deployment.
The product context also explains why field work is part of the internship. Since the system depends on live garment units, the intern will need to visit the field for calibration and ground-truth collection. This ensures that the algorithms are validated against manual floor counts and can adapt to real production conditions. In short, the internship sits at the intersection of sensor data, production measurement, and finance enablement for MSMEs.
What Nool is building
- IoT sensors on sewing machines in textile and garment MSMEs.
- Data pipelines that turn stitch-level signals into production counts.
- A financial stack that uses live production output.
- Support for working capital and machinery financing.
- Infrastructure for nano job-work units using verifiable production data.
Internship Overview, Duration, and Stipend
The advertised role is Data Science Intern for Nool by Firgun Labs. The internship is listed as a work from home opportunity, but it also requires field visits for sensor calibration and ground-truth collection. The primary option is a 3-month internship with a stipend of Rs. 25,000 – 35,000 per month. There is 1 opening, and the internship can begin immediately for candidates who can start between 22 July 2026 and 26 August 2026.
The listing also shows multiple stipend and duration options, so applicants should check the Internshala page carefully before applying. Alongside the main 3-month option, the listing includes a 6-month option with Rs. 20,000 – 40,000 per month, a 1-month option with Rs. 4,000 – 5,000 per month, and a 1-month unpaid option. The content provided identifies the 3-month version as the main advertised option, but the exact preference should be confirmed on the listing.
The application deadline is 21 August 2026, and applications are to be submitted through Internshala. Since the role is tied to live sensor calibration and production validation, the internship is designed for someone who can combine remote work with on-ground visits when needed. That combination is central to the nature of the assignment and should be considered by anyone applying.
| Key Detail | Information |
|---|---|
| Role | Data Science Intern |
| Company | Firgun Labs |
| Product | Nool |
| Location | Work from home, with field visits required |
| Duration | 3 months (primary option) |
| Stipend | Rs. 25,000 – 35,000 per month |
| Openings | 1 |
| Apply by | 21 August 2026 |
Day-to-Day Responsibilities and Project Scope
The internship responsibilities are highly technical and focused on building a production-counting system from raw sensor data. The first major task is to build an algorithm that converts raw 0/1 sewing-machine sensor data into a daily garment count. This is the core data science problem in the role, and it directly supports the product’s goal of measuring production output from live machine activity. The intern will also work with IoT sensor data from a live garment unit, which is why field visits are required for calibration and ground-truth collection.
A second major responsibility is to build a segmentation pipeline that groups machine runs into piece-cycles using adaptive gap-threshold learning. The content specifically mentions GMM + PELT via the ruptures library, which indicates that changepoint detection and sequence segmentation are part of the work. This is not a generic internship task; it is a focused effort to identify production cycles from noisy or continuous sensor signals. The goal is to make the count reliable enough to reflect actual garment output.
The role also includes building a calibration system that learns per-station ratios and thresholds, validated against manual floor counts. This means the intern will not only create algorithms, but also tune them against real-world observations from the floor. Another responsibility is style-change detection, so the system can automatically recognize when the production line switches garment styles and reconfigure without manual input. Finally, the intern will help deploy a scheduled Python processing worker and a FastAPI backend that serves a supervisor dashboard with live counts and WIP alerts.
Core responsibilities at a glance
- Convert raw 0/1 sensor data into daily garment counts.
- Work with live IoT sensor data from a garment unit.
- Build segmentation using adaptive gap-threshold learning.
- Implement calibration against manual floor counts.
- Detect style changes automatically.
- Deploy a Python worker and FastAPI backend for live monitoring.
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Skills, Tech Stack, and Eligibility
The internship calls for a strong foundation in Artificial Intelligence, Data Analytics, Data Science, Feature Engineering, Machine Learning, Python, and SQL. The requirements emphasize practical capability with Python, time-series data, basic statistics, and SQL. These are the must-have skills because the role involves working with sensor streams, segmentation, calibration, and backend processing. The work is therefore suited to someone who is comfortable moving between data analysis and implementation.
The good-to-have skills include IoT or sensor data experience, FastAPI, and changepoint detection. The tech stack listed for the role includes Python with pandas, numpy, scipy, ruptures, and stumpy, along with FastAPI and PostgreSQL + TimescaleDB. This stack reflects the full workflow of the internship: ingesting and processing sensor data, detecting changes in production patterns, and serving results through a backend system.
Eligibility is straightforward and tied to availability. Applicants should be available for the work-from-home internship with required field visits, should be able to start between 22 July 2026 and 26 August 2026, and should be available for a duration of 3 months. The content also notes that women wanting to start or restart their career are encouraged to apply. Since the role is specialized, relevant skills and interests are important for consideration.
Requirements and tech stack
- Must-have: strong Python, time-series data experience, basic statistics, and SQL.
- Good-to-have: IoT/sensor data experience, FastAPI, and changepoint detection.
- Tech stack: Python, pandas, numpy, scipy, ruptures, stumpy.
- Backend and database: FastAPI, PostgreSQL, and TimescaleDB.
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How to Apply and What to Expect
Applications for the internship are submitted online through Internshala. To apply, candidates should open the internship page, log in to or create an Internshala account, complete the application, and submit it before the deadline of 21 August 2026. The apply link provided for the listing should be used directly for the application process. Since there is only 1 opening, applicants should pay close attention to the deadline and the listed eligibility requirements.
The internship is especially relevant for candidates who want hands-on work with sensor data, production analytics, and backend deployment. Because the role includes field visits, the experience is not limited to remote analysis; it also includes calibration and ground-truth collection in a live garment unit. That makes the internship practical and operational, with a direct connection between data science work and real production outcomes. The supervisor dashboard with live counts and WIP alerts also suggests that the work has a visible product-facing output.
Applicants should also note the multiple stipend options shown in the listing. The main advertised option is the 3-month internship at Rs. 25,000 – 35,000 per month, but the listing also includes the 6-month, 1-month paid, and 1-month unpaid options. Checking the Internshala page is the best way to confirm the exact option you want before submitting the application.
Application essentials
- Open the internship page on Internshala.
- Log in to or create your Internshala account.
- Complete the application form.
- Submit before 21 August 2026.
Frequently Asked Questions
What is the role offered by Firgun Labs?
The role is a Data Science Intern position for Nool by Firgun Labs. It focuses on building algorithms that convert raw sewing-machine sensor signals into reliable production counts for textile and garment MSMEs. The internship is work from home, but field visits are required for calibration and ground-truth collection.
What is the duration and stipend for the main option?
The primary advertised option is a 3-month internship with a stipend of Rs. 25,000 – 35,000 per month. The listing also shows other options, including a 6-month paid option, a 1-month paid option, and a 1-month unpaid option. The exact option should be checked on the Internshala listing.
What kind of work will the intern do?
The intern will build an algorithm for daily garment counts from raw 0/1 sensor data, create a segmentation pipeline, implement calibration against manual floor counts, detect style changes, and help deploy a Python worker and FastAPI backend. The work is centered on live IoT sensor data from a garment unit and on making production counts reliable.
Who can apply for this internship?
Applicants should be available for the work-from-home internship with required field visits, able to start between 22 July 2026 and 26 August 2026, and available for 3 months. Relevant skills and interests are important, and women wanting to start or restart their career are also encouraged to apply.
What skills are required?
The must-have skills are strong Python, time-series data experience, basic statistics, and SQL. Good-to-have skills include IoT or sensor data experience, FastAPI, and changepoint detection. The listed tech stack includes Python, pandas, numpy, scipy, ruptures, stumpy, FastAPI, PostgreSQL, and TimescaleDB.
How do I apply?
Applications are submitted online through Internshala. Candidates should open the internship page, log in to or create an account, complete the application, and submit it before 21 August 2026. The apply link provided in the listing should be used for the application process.
Conclusion
The Data Science Internship at Firgun Labs is a focused opportunity for candidates who want to work on real sensor data, production analytics, and backend systems for MSMEs. Through Nool, the company is turning sewing-machine activity into measurable production output and using that data to support finance access for textile and apparel units. The role combines remote work with required field visits, making it both analytical and hands-on. With one opening, a clear deadline, and a defined technical scope, this internship is structured for someone ready to work on practical data science in a live industrial setting.
