Become an integral part of our Quant Analytics team! Each day will be unique – bring a positive attitude, entrepreneurial spirit and get ready to roll up your sleeves. This position is an essential part of the team and will have exposure to several aspects of running a banking office.

Job Summary:

As a Quant Analytics at JPMorgan Chase within the Consumer & Community Banking- Data and Analytics, you serve as a seasoned member of an agile team to design and deliver trusted market-leading technology products in a secure, stable, and scalable way. You are responsible for carrying out critical technology solutions across multiple technical areas within various business functions in support of the firm’s business objectives.

Job Responsibilities: 

Independently own the development and reporting of Ops performance metrics and KPIs. Use analytical tools and quantitative methods such as trend analysis, segmentation, forecasting, optimization, and other techniques to improve business function performance. Build a suite of reports that allows Product Owners and Leadership to view productivity and scorecard metrics associated with Knowledge Management usage and tracking business outcomes generated. Create behavioral analytics to understand specialists and personalize their experience. Proactively identify opportunities to automate manual data processing and reporting steps using workflow automation tools and visualization tools. Support and lead partnerships with key Ops stakeholders and Ops Product groups focusing on MLIO Knowledge Management with a strong understanding of business drivers, underlying data, and processes. Prepare and deliver presentations summarizing sharp insights and conclusions, often for executives, leadership teams, and business partners in regularly scheduled analytics meetings. Transform data, reporting, and analysis into insights that improve existing operational processes and applications impacting thousands of front-line specialists. Identify, test, and deploy new data types that can provide insights and enhance existing prediction capabilities to offer analytical recommendations aligning with core objectives. Proactively investigate issues and problems in both model building and production phases, and document KPI, PoC, workflow, and data sources in a clear and concise way.

Required qualifications, capabilities and skills:

Bachelors or Master's degree in a quantitative or related field Hands-on experience with standard data analytics tools and technologies - SQL, Python, Tableau, Alteryx, R etc.  Experience delivering analytics solutions under strict timelines quick turn-around time Knowledge of advanced statistical methodologies and ML techniques – Linear/Logistic Regression, Clustering, Classification techniques such as Random Forest, Gradient Boosting, and text mining techniques Experience working in cloud tech stack: AWS, Snowflake, Azure etc. Comfortable making decisions under uncertainty and ambiguity, and proven ability to structure problems and develop analytical frameworks while addressing business and technical risks Self-motivated, goal-oriented, and able to manage and deliver in an innovation-driven and fast-paced environment Leadership drive, ability to analyze problems, design solutions, and communicate effectively and confidently with relevant stakeholders to influence and gain buy-in across various job functions Flexibility/adaptability, ability to listen and defend or change direction based upon team and stakeholder consensus Superior judgment to mitigate risk, and to foster an environment where risk/control issues are escalated and trends are anticipated and identified Acting with integrity, and protecting our company, clients and customers

Preferred qualifications, capabilities and skills:

9+ years of related experience in Analytics, preferably with financial services firms and/or in Operations/contact center functions Hands-on experience writing code and automating processes to source, transform and analyze data from multiple sources including structured and unstructured data preferred Strong Statistical Knowledge preferably with practical experience in conducting controlled experiments – A/B Tests, Causal Inference, Synthetic Control, Diff in Diff tests etc.  Should have a very good understanding of IT processes and databases. Should be able to work directly with data owners/custodians and contribute in building analytics data hub