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Fintech and BFSI hiring in Bengaluru
The full Bengaluru market picture across fintechs, product firms and financial services GCCs, and every function we run here.
Bengaluru hiringSpecialist recruitment for data scientists in credit and risk modelling, fraud and financial crime analytics, and payments across banks, NBFCs, fintechs and GCCs in Bengaluru. We source people who have worked inside the domain. Success-fee, paid only on joining.
Brief us on a data science roleBengaluru holds the deepest data and machine learning pool in India, and a large share of the financial services GCC data teams are based in the city, which gives it real strength in credit, fraud and payments modelling. The abundance is also the trap: the volume of data scientists here is high, but the slice that has worked inside regulated financial workflows is narrow, and it is fought over by funded product firms, captives and the banks themselves.
Financial services data science carries a context that generalist data work does not. The job sits inside portfolio structures, regulatory-reporting cadence, and model governance, and it turns on the difference between a model that is accurate and one that a regulator and a model-risk committee will actually accept. A strong data scientist from consumer internet or marketing analytics can be genuinely capable and still need that context explained on the job, which in a lending or risk function is slow and expensive. We source the people who already carry it, and calibrate the brief so you are not paying a premium for a profile that will not clear model governance.
Domain, not just technique. Lending, risk, fraud or payments experience, with an understanding of portfolio and regulatory context, rather than a strong but domain-agnostic modelling record.
Models that shipped and held. We look for models that went into production and survived governance and monitoring, not notebooks that never left research.
Governance literacy. Model documentation, validation, and the discipline a regulated environment requires. This is where generalist hires most often struggle.
Fit for your maturity. A data scientist who can build a function from scratch is a different hire from one who optimises a mature modelling stack. We match to where your data capability actually is.
Compensation runs wide with seniority, modelling discipline and employer type, with GCC and product-firm competition pulling the top of the band up. We publish current numbers so an offer is built on live data. See the data scientist salary guide for financial services, and the 2026 technology compensation pillar for the wider market.
Data scientists, machine learning engineers, and data science leads and managers working in credit and risk modelling, fraud and financial crime analytics, collections, and payments and lending data science, across banks, NBFCs, fintechs and the financial services GCCs concentrated in the city.
A data scientist in lending or risk works inside portfolio structures, regulatory-reporting cadence, model governance and the difference between a model that is accurate and one a regulator will accept. A strong generalist from a consumer-internet or marketing analytics background usually needs that context explained on the job. We source people who have already worked inside lending, risk, fraud or payments.
Yes. Bengaluru has the deepest data and machine learning pool in India, and a large share of the financial services GCC data teams sit here, which means real depth in credit, fraud and payments modelling. The competition for that slice is intense, so the work is identifying and engaging domain-literate data scientists before funded product firms and captives do. See the national view of the search.
Compensation runs wide with seniority, modelling discipline and employer type. We publish a current data scientist salary guide for financial services from live mandate data, so an offer can be built on this quarter's numbers rather than a dated survey.
City
The full Bengaluru market picture across fintechs, product firms and financial services GCCs, and every function we run here.
Bengaluru hiringNational role
The national view of the data science search in financial services: domain fit, model governance, and how the mandate runs.
Data scientist hiringAdjacent role
The engineering teams your data science function ships with, screened for regulated-workflow depth, in the same market.
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