What the role involves
About Nanonets
Nanonets has a vision to help computers see the world starting with reading and understanding documents. Machine Learning (ML) is no longer a futuristic concept—it's a present-day powerhouse transforming the business landscape. Nanonets is at the forefront of this transformation, offering innovative ML solutions designed to make document-related processes faster than ever before.
From automating data extraction processes to enhancing reconciliation, our solutions are designed to revolutionize workflows, optimize operations, and unlock untapped potential for our clients. Our client footprint spans across brands such as Toyota, Boston Scientific, Bill.com and Entergy to name a few enabling businesses across a myriad of industries to unlock the potential of their visual and textual data.
We recently announced a series B round of $29 million in funding by Accel and are backed by the likes of existing investors including Elevation Capital and YCombinator. This infusion of capital underscores our commitment to driving innovation and expanding our reach in delivering cutting-edge AI solutions to businesses worldwide.
Read about the release here
<u><a href="https://www.forbes.com/sites/davidprosser/2024/03/12/why-enterprises-are-learning-to-love-nan" target="_blank">https://www.forbes.com/sites/davidprosser/2024/03/12/why-enterprises-are-learning-to-love-nanonets-automation/?sh=6d79ec8f3ca1</a></u>
<u><a href="https://techcrunch.com/2024/03/12/nanonets-funding-accel-india/amp/" target="_blank">https://techcrunch.com/2024/03/12/nanonets-funding-accel-india/amp/</a></u>
We’re on a mission to hire the very best and are committed to creating exceptional employee experiences where everyone is respected and has access to equal opportunity.
Role Overview
We are seeking a Product Analyst to take ownership of key metrics, reporting, and experimentation within Nanonets. Working directly with our founders, this role involves goal setting, tracking, and prioritizing features based on metrics-driven insights. As a Product Analyst, you’ll be critical to helping teams set data-informed goals, clarifying the key metrics that drive success, and enabling a hypothesis-driven approach to product development.
Key Responsibilities
- Metrics Ownership: Manage and report on company metrics, setting measurable goals and tracking progress against them.
- Outcome Definition: Help teams define data-backed goals and establish measurable outcomes, ensuring efforts align with strategic company objectives.
- Input Metrics Clarity: Identify and communicate the key levers that drive output metrics, providing teams with actionable insights.
- Hypothesis-Driven Development: Build systems that support hypothesis testing through product features, creating, running, and measuring A/B tests and experiments to validate customer behavior hypotheses.
- Product Development Optimization: Partner with product teams to establish high-quality goals, focus on the most impactful metrics, and support agile development based on data-driven decision-making.
What We’re Looking For
Education
- Bachelor’s degree preferable from a Tier 1 college.
- 2-4 years of relevant experience, such as Data Analyst or Product Analyst, ideally within a B2B SaaS company.
Technical Skills
- Proficiency in SQL (required).
- Strong analytical skills and understanding of key product metrics.
- Willingness to learn Python and enhance data engineering skills.
- Robust product sense, with the ability to interpret and act on data for feature prioritization.
- Mindset : Curious, experiment-driven, and eager to tackle complex product challenges through data. Comfortable scrapping or iterating on underperforming features based on data.
- Why Join Us?
- Innovative Culture: Be part of a forward-thinking company at the forefront of AI and ML innovation.
- Growth Opportunities: Nanonets offers ample growth opportunities, allowing you to make a tangible impact in the product features
- Flexible Work Arrangements: Enjoy a fle
About NanoNets
AI agents break where it matters most: when the details are buried in an invoice, a BoL, or a clinical document. Most agents guess. They hallucinate field values, apply rules inconsistently, and when something goes wrong, you can’t tell why or fix it without redoing the work yourself. Nanonets is built differently. Every extraction is traceable. You can see exactly what the agent read, what rule it applied, and why it made the call it did. When it’s uncertain, it flags the right thing for human review instead of silently getting it wrong. When you correct it, it learns. When you add business rules, it tracks which rule drove which decision. Anyone can build agentic workflows, but AI agents are black boxes that struggle with complex files and processes, like POs, invoices, BoLs and clinical documents. Nanonets agents understand key details in files, work through complex processes and act with transparency, making them the most reliable foundation for building workflows where details matter. Nanonets reduces processing time by 95% by automating messy manual processes and delivering clean data to systems of record like SAP, SFDC and more. That’s why Nanonets is the automation layer global enterprises reach for when accuracy is non-negotiable.
Full NanoNets profile