JPMorgan Chase
From JPMorgan Chase's careers page
Status: listed on the employer's own careers page when we last checked (daily). Confirm on their site before applying.
You are a strategic thinker passionate about driving solutions in Financial Analytics, Reporting, Business Intelligence, Data Science (EDA and Modelling) and AI / Gen AI. You have found the right team.
As a Financial Analytics Associate within our Asset and Wealth Management Transformation and Analytics Team, you will define, refine, and deliver strategic goals for our firm by translating complex financial and operational data into actionable insights, predictive models, and AI-promoten solutions that enhance decision-making and promote business performance.
Scope, prioritize and co-ordinate activities with product owners and finance stakeholders. Partner with Finance, Risk and Business teams to identify strategic analytical, data science and AI solutions. Perform in-depth financial analysis including revenue, expense, margin, variance, profitability, product/client profitability and KPI analysis to support business decisions.
Design, develop and automate management reporting, dashboards and scorecards covering P&L, balance sheet, cash flow, forecasts, budgets, headcount and performance metrics. Drive the annual budgeting, mid-year re-forecast, rolling forecast and multi-year strategic planning cycles in partnership with Business Finance teams.
Implement exploratory data analysis (EDA) and statistical modelling to identify trends, patterns and drivers of financial performance. Identify key financial and operational data sources that can drive business impact; ensure data quality, reconciliation and audit trails across reporting outputs.
Design and develop data mining and reporting queries from large data sets (both structured and unstructured) and convert raw financial data into clear information. Build compelling visualizations and storytelling using BI tools (Tableau, Power BI, Alteryx) that translate financial results and model outputs into clear business narratives for senior leadership.
Employ scaling and automation to data preparation, consolidation and reporting workflows to improve efficiency and accuracy of recurring financial deliverables. Transform model outputs and analytical results into formats digestible to end users through visualizations, clear tables and thoughtful presentations; assist technical and non-technical stakeholders in interpreting the analysis.
Leverage AI assistants and copilots (e.g., Microsoft 365 Copilot, GitHub Copilot, and in-house Gen AI tooling) to accelerate analytics workflows — code generation, SQL/Python drafting, document summarization, and natural-language querying of financial datasets — while applying firm-approved controls on data confidentiality and model output review.
Required qualifications, capabilities and skills
Self-starter, attention to detail and results oriented, able to work under minimal guidance in a fast-paced environment.
Uses pertinent financial data and facts to identify and solve a range of business problems within area of expertise.
Mandatory experience in financial analytics, FP&A, management reporting, variance analysis and KPI/performance measurement. Strong understanding of accounting principles (US GAAP / IFRS), financial statements (P&L, balance sheet, cash flow), journal entries, intercompany, allocations, accruals and month-end close processes.
Working knowledge of profitability and performance metrics: unit economics, gross/operating margin, contribution margin, EBITDA, ROE/ROA, cost-to-income ratio, NIM, fee revenue and AUM-based metrics.
Mandatory experience in Exploratory Data Analysis (EDA), regression and statistical/machine learning modelling applied to financial or business datasets. Hands-on experience with pandas and PySpark/PySQL stack. Experience in building data extraction, transformation and modelling pipelines.
Strong proficiency in SQL (Snowflake, Databricks) and Python (Pandas, NumPy, Scikit-learn, Keras, PySpark/PySQL) for data wrangling, modelling, AI pipelines and automation of financial workflows. Hands-on experience using AI skills / copilots to support analytics work — e.g., Microsoft 365 Copilot (Excel, Power BI, Word, PowerPoint), GitHub Copilot, for SQL generation, data summarization and productivity gains in day-to-day financial analytics deliverables; awareness of responsible-AI, data-privacy and model-risk guardrails.
Working proficiency in data visualization tools; strong experience with BI technologies including but not limited to Tableau, Power BI and Alteryx. Experience in end-to-end implementation of Business Intelligence (BI) reports and dashboards for finance, risk or business performance reporting. Should be good at mathematics, inferential statistics and quantitative analysis as applied to financial data and model building.
Provides explanations and information to others on topics within area of expertise; strong business partnering skills with Finance and Business stakeholders.
Experience Required: 5+ years in data/analytics related projects with 2+ years in financial analytics
Good communication and analytical skills, with the ability to present financial insights, model results and AI-driven outputs clearly to senior stakeholders.
Bachelor's Degree in Finance, Accounting, Economics, Statistics, Data Science, Computer Science or Engineering. A different field of study with significant professional experience in Financial Analytics / BI / Data Science / AI is acceptable. MBA (Finance) is a strong plus.
Exposure to Asset & Wealth Management / banking products and metrics (AUM, net flows, revenue yield, client profitability, fee waivers) is strongly preferred.
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