Bulge Bracket Investment Banks

Quant Analytics Associate

at J.P. Morgan

Mid LevelNo visa sponsorshipData Science/AI/ML

Posted a day ago

No clicks

Compensation: Not specified
City: Bengaluru
Country: Not specified

Join our Operations Data and Analytics team in Bengaluru to shape quant-driven solutions that improve Knowledge Management and performance at scale. Design and deliver trusted, scalable analytics that translate complex data into clear insights and measurable business outcomes for thousands of front-line specialists. Collaborate across product, operations, and technology in an agile, inclusive culture that values curiosity, precision, and continuous improvement. The role emphasizes developing dashboards, forecasting, and building predictive capabilities to power Knowledge Management initiatives.

Location: Bengaluru, Karnataka, India

Join our Operations Data and Analytics team to shape quant-driven solutions that improve Knowledge Management and performance at scale. Grow your skills and impact in a supportive, high-visibility environment.

As a Quant Analytics Associate wihin the Operations Data and Analytics team, you design and deliver trusted, scalable analytics that power Knowledge Management and operational excellence. You collaborate across product, operations, and technology to translate complex data into clear insights and measurable business outcomes for thousands of front-line specialists. You work within an agile, inclusive culture that values curiosity, precision, and continuous improvement.

Job responsibilities

Owns the development and reporting of performance metrics and key performance indicators, applying trend analysis, segmentation, forecasting, optimization, and related quantitative techniques to improve operational performance

Builds and maintains reporting suites and dashboards that enable product owners and leaders to monitor productivity, scorecards, and outcomes from Knowledge Management usage

Creates behavioral analytics to understand specialist behavior and personalize experiences across channels

Automates manual data processing and reporting using workflow automation and visualization tools to increase efficiency and accuracy

Leads partnerships with Operations stakeholders and product teams on Knowledge Management initiatives, grounded in strong knowledge of business drivers, data, and processes

Prepares and delivers executive-ready presentations that synthesize complex analyses into clear insights and actions; transforms data into recommendations that improve processes and applications for front-line specialists

Identifies, tests, and deploys new data sources to enhance predictive capabilities; investigates and resolves issues in model development and production, and documents key performance indicators, proofs of concept, workflows, and data sources

Required qualifications, capabilities, and skills

Bachelor’s degree in Economics, Data Analytics, Statistics, or a STEM field and 4+ years of analytics experience.

Proficient in SQL with solid programming skills for data querying and transformation

Experience with big data ETL for structured and unstructured datasets

Training in multivariate statistics and regression methods, with applied experience in analytics and visualization including Spark

Hands-on experience with data wrangling and visualization tools, including Excel PivotTables, Tableau, Alteryx, and Jupyter Notebook, and presentation development in PowerPoint

Practical experience with cloud and data platforms and tooling, including AWS, Spark/EMR, Snowflake, and collaboration tools such as Confluence; familiarity with generative AI tools such as ChatGPT

Strong written and verbal communication skills; detail-oriented problem solver who meets tight deadlines and operates with curiosity in a self-directed, team-oriented environment

Preferred qualifications, capabilities, and skills

Extensive experience in consumer banking domains such as operations, servicing, collections, or marketing

Solid foundation in advanced analytics methods, including multivariate and logistic regression, clustering and classification, controlled experiments, and causal inference techniques such as difference-in-differences, propensity matching, and nearest neighbor methods

Strong understanding of IT processes and databases; ability to work directly with data owners and custodians and contribute to building an analytics data hub

Flexibility and adaptability; able to listen, and confidently defend or adjust direction based on team and stakeholder consensus

Design analytics and reporting to power Knowledge Management and Operations performance across consumer banking.

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