Data Analyst, Finance and Payments
Handshake · Bengaluru, Karnataka
- Location
- Bengaluru, Karnataka, India
- Employment
- Full time
- Level
- Mid level
- Posted
- 3 weeks ago
About this role
About Handshake
Handshake was founded on a simple belief that everyone deserves a path to a great career, regardless of where they went to school or who they know. Today, we power 25 million job seekers, 1 million+ employers, and 1,600 educational institutions.
In 2025, we started Handshake AI and built the fastest-growing AI data business in history. We work directly with frontier AI lab researchers to create evaluations, publish benchmarks, and push the boundary of data. We’ve grown from $0 to ~$1B run rate and pay ~$60M to over 30K individuals every month.
Why join Handshake now:
Shape how every career evolves in the AI economy, at global scale, with impact your friends, family and peers can see and feel
Partner hand-in-hand with world-class AI labs, Fortune 500 partners and the world’s top educational institutions
Work together with engineers, scientists, operators, and more from Palantir, Meta, Scale AI, and former YC founders
Build a massive, fast-growing business with billions in revenue
About Handshake AI
Human data is the core infrastructure to AI advancement. Frontier AI labs currently improve model capabilities with various data-intensive post-training techniques. We believe that data spend for AI training will increase by 3-5x in the next few years and continue for much longer as models take on new domains. Handshake AI supports all of the frontier AI labs, working on their most complex data at the largest scale.
About the Role:
We are looking for a Data Analyst to support the Finance and Central Operations organization and help build the data infrastructure, reporting, and analytics that power financial and operational decision-making.
This role combines analytics, data engineering, and applied data science, with a strong focus on translating complex operational data into reliable financial insights. While reporting within the Finance team, this role will also partner closely with the Payment Operations team, helping improve the data, controls, and automation behind high-volume payment processes.
This role requires close collaboration with our San Francisco - based team and availability during core U.S. business hours.
Desired Capabilities:
3 - 6+ years of experience in data analytics, analytics engineering, data engineering, financial analytics, or a related field.
Build and maintain scalable Finance and Operations dashboards and reporting across revenue, project expenses, margins, cash flows, payments, and other key financial and operational metrics.
Develop automated data pipelines across systems that bring together information from financial, operational, and business systems.
Identify and execute opportunities to automate existing financial reporting processes, reducing manual effort and improving the consistency and reliability of recurring deliverables.
Contribute to the buildout of finance data infrastructure, automate recurring reporting, and reduce reliance on manual, spreadsheet-based processes.
Partner with Payment Operations to build reporting and analytics around payment volumes, accuracy, exceptions, disputes, and processing performance.
Develop automated reconciliations and controls to identify missing, duplicate, incorrect, or unusual payments.
Support the investigation and resolution of payment discrepancies through data analysis.
Help improve and automate payment workflows, including data validation and exception management.
Partner with Finance and Operations stakeholders to translate business questions into data models, dashboards, and actionable analysis.
Establish documentation, data definitions, and controls that improve the reliability and auditability of Finance and Payments reporting.
Experience with Python or another analytical programming language.
Extra Credit:
Advanced SQL skills and experience working with large datasets.
Experience building dashboards and reporting using tools such as Hex, Looker, Tableau, Power BI, or similar.
Familiarity with modern data warehouses and transformation tools such as Snowflake, BigQuery, Databricks, or similar.
Strong understanding of data modeling, data quality, reconciliation, and automation.
Ability to understand financial and operational processes and translate them into technical solutions.
Strong analytical mindset and ability to independently investigate discrepancies and ambiguous data problems.
Experience working with Finance teams strongly preferred.
Experience with payment operations, high-volume contractor payments, or other transaction-heavy environments is a plus.
Perks:
Generous equity grant, vested over 4 years
Well-defined performance bonus ranging between 10 - 100% of base
Premium medical insurance coverage
Food credit for every in-person day
As published by Handshake. Applications are handled on their site.
Skills this posting mentions
About Handshake
Handshake is the career network for the AI economy. 20 million knowledge workers, 1,600 educational institutions, 1 million employers (including 100% of the Fortune 500), and every foundational AI lab trust Handshake to power career discovery, hiring, and upskilling, from freelance AI training gigs to first internships to full-time careers and beyond.
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Apply to Handshake with a resume written for this role.
Queue Data Analyst, Finance and Payments and I read the posting, rewrite your resume against it, draft the cover letter, and score the fit. Then you press send, or press one button and I fill in Handshake’s form for you.
01Drop your resume
A PDF or a LinkedIn URL. About a minute, once.
02I rank the openings
Every weekday morning, the live catalog scored against your history. Up to 20 worth your time, not two hundred links.
03Each one is written up
Resume rewritten for the posting, a cover letter, a fit score. Press send, or let me fill in the form.
- 25 sent a week, free
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Paste your career in once. Every application after that is written for you.
Drop a resume or a LinkedIn URL. I rank the live openings against it, rewrite the resume and write a cover letter for the best of them, and fill in the employer's form when you press the button. You read, you decide what goes out.
01Drop your resume
A PDF or a LinkedIn URL. About a minute, once.
02I rank the openings
Every weekday morning, the live catalog scored against your history. Up to 20 worth your time, not two hundred links.
03Each one is written up
Resume rewritten for the posting, a cover letter, a fit score. Press send, or let me fill in the form.
- New matches ranked and written before you are up.
- Every bullet stays inside what your history supports. Nothing invented.
- Queued, submitted, interviewing, offer: one screen, not a spreadsheet.
500 free credits on sign-up. No card. Nothing is sent until you say so.
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