AI Control Manager Associate at JPMC Candidate Experience page

Bengaluru, karnataka, India -

Full Time

Start Date

Immediate

Expiry Date

13 Jul, 26

Salary

0.0

Posted On

14 Apr, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Python, R, Machine Learning, Generative AI, Data Analysis, Risk Management, Automation, Alteryx, Power BI, Tableau, Regulatory Compliance, Control Testing, Statistical Analysis, Data Governance, Financial Services, Audit

Industry

Financial Services

Description

Join a high‑impact Strategic Control Testing team shaping a best‑in‑class onboarding and documentation experience across global regions. Collaborate with WKO, DDS, and cross‑functional partners to embed data, AI, and automation into controls that scale. Grow your career by delivering measurable risk reduction, stronger compliance, and operational resilience. As a Data & AI Control Manager within the Strategic Control Testing group in OCM, you design and execute data‑driven control testing across Client Onboarding & Documentation, including WKO and DDS. You build automation and apply AI/ML—including Generative AI—to enhance risk detection, continuous monitoring, and regulatory compliance. You partner across businesses and Corporate Functions to close control gaps, uplift resilience, and maintain audit‑ready evidence. Job Responsibilities * Lead strategic control testing engagements using analytics to surface gaps and BAU breaks; drive actionable remediation. * Build and productionize AI/ML solutions (classification, anomaly detection, risk scoring, entity resolution) and GenAI workflows. * Automate end‑to‑end testing and control processes with Alteryx, Power BI/Tableau, and workflow/RPA platforms. * Operationalize proactive alerts and dashboards for KRIs and regulatory priorities. * Partner with WKO, DDS, Controls, Operations, Technology, and Data teams to define requirements and ensure explainability/auditability. * Maintain high‑quality reporting and executive summaries on trends, systemic issues, and control weaknesses. * Stay current on LLMs/GenAI and advanced ML; identify high‑value use cases with appropriate guardrails. * Design statistical tests and ML‑based monitors for policy, legal, and regulatory compliance aligned to audit and model risk governance. * Build pipelines to ingest, profile, cleanse, and join large datasets from systems of record for repeatable analytics. * Apply LLMs/GenAI for document parsing, policy mapping, and exception narrative synthesis using RAG and prompt engineering. * Translate KYC/CO&D requirements into measurable tests and rules; tune to reduce false positives and document methods for audits. Required Qualifications, Capabilities, and Skills * Hold a bachelor’s or advanced degree in a quantitative field (Computer Science, Statistics, Engineering, Data Science). * Bring 6+ years in risk management/financial services across compliance, financial crimes, operational risk, audit, or BPM with automation/modeling exposure. * Demonstrate proficiency in Python or R for data manipulation, model development, and testing automation at scale. * Apply modern ML, pattern recognition, and statistical analysis with clear understanding of limitations in regulated environments. * Consume APIs and integrate diverse data sources while adhering to data governance, lineage, and quality standards. * Execute control testing with strong control design, root cause analysis, and documentation discipline. * Partner across business, operations, and technology to deliver measurable risk and control outcomes. Preferred Qualifications, Capabilities, and Skills * Leverage hands‑on experience with LLMs/GenAI and ML techniques for predictive modeling and monitoring. * Utilize advanced analytics (regression, classification, clustering, dimensionality reduction) to improve control effectiveness. * Manage 2–3 automation initiatives concurrently across global teams and time zones with clear governance. * Strengthen compliance by aligning evidence to audit and model risk standards and ensuring explainability. * Enhance data reliability via metadata, lineage tracking, and secure usage aligned to regulatory requirements. * Communicate complex findings through concise executive summaries, dashboards, and stakeholder forums. * Institutionalize lessons learned via playbooks, standardized test scripts, and reusable control components. JPMorganChase, one of the oldest financial institutions, offers innovative financial solutions to millions of consumers, small businesses and many of the world’s most prominent corporate, institutional and government clients under the J.P. Morgan and Chase brands. Our history spans over 200 years and today we are a leader in investment banking, consumer and small business banking, commercial banking, financial transaction processing and asset management. We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants’ and employees’ religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs [https://careers.jpmorgan.com/us/en/how-we-hire/faqs] for more information about requesting an accommodation. J.P. Morgan’s Commercial & Investment Bank is a global leader across banking, markets, securities services and payments. Corporations, governments and institutions throughout the world entrust us with their business in more than 100 countries. The Commercial & Investment Bank provides strategic advice, raises capital, manages risk and extends liquidity in markets around the world.

Responsibilities

The AI Control Manager Associate will design and execute data-driven control testing and build AI/ML solutions to enhance risk detection and regulatory compliance. They will partner with cross-functional teams to automate testing processes and maintain audit-ready evidence for global operations.