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Salary
$18k – $43k per year (Estimated)
Location
In office (Bengaluru)
Seniority
Junior · 2+ years exp
Overview
Company
Impact
Profile match
JPMorganChase is the largest bank in the United States by assets and one of the most systemically important financial institutions in the world, with a lineage running back through more than a thousand predecessor firms to the 1799 founding of the Bank of the Manhattan Company. It combines a dominant investment bank and markets business with Chase, the largest retail banking franchise in America, plus commercial banking and asset and wealth management. Headquartered in New York, the group is unusual among banks for the scale of its technology spending, running one of the largest engineering organisations of any financial institution and deploying its own internal AI platform across the firm.

You are a strategic thinker passionate about driving solutions in Data Analytics. You have found the right team.

As a Quant Analyst in our Finance team, you will spend each day defining, refining and delivering set goals for our firm. you will perform foundational analysis across branch performance data to identify trends, surface anomalies, and inform new questions and actions. You partner with finance and business stakeholders to define data requirements, ensure data quality and integrity across sources, and translate business definitions into durable datasets.

Using strong SQL and Python skills, you support the development of standardized metrics, recurring reporting, and dashboards that enable consistent, timely, and well-governed insights for Branch Performance.

Job responsibilities

- Gather, extract, and prepare branch network and occupancy cost data from legacy sources and Databricks for finance reporting and analysis.

- Develop and maintain SQL queries and Python-based workflows to support recurring reporting, ad-hoc analysis, and data validation.

- Understand and document data definitions, business rules, and source-to-target mappings to support legacy-to-Databricks transition and ongoing lineage clarity.

- Perform reconciliations between legacy outputs and Databricks datasets; investigate and explain variances, identify root causes, and track issues through resolution.

- Support finance partners by translating questions into clear analytical requirements and producing accurate, explainable outputs aligned to finance definitions.

- Contribute to dashboards and visualization deliverables where needed (e.g., ThoughtSpot), and support process improvements to reduce manual reporting effort.

- Apply data controls and governance standards, including documentation, validation checks, and change traceability.

Required qualifications, capabilities, and skills

- 2+ years of experience in data analysis, reporting, business intelligence, or an analytical finance support role.

- Strong proficiency in SQL and Python (data extraction, transformation, reconciliation, and analysis).

- Demonstrated experience working with complex datasets across multiple systems and resolving inconsistencies in definitions and outputs.

- Ability to structure and communicate analysis clearly to finance and non-technical stakeholders.

- Strong Microsoft Excel skills for analysis and validation.

- Experience with one or many Intelligent Automation tools

- Exposure to financial cost concepts such as P&L Statement, occupancy cost components, allocations, cost center structures, and reporting hierarchies.

- Bachelor’s degree or equivalent experience.

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