Advanced Analytics Associate

Advanced Analytics Associate

You are a strategic thinker passionate about driving solutions in Advanced Analytics, AI/ML, and data-driven marketing. You have found the right team.

As an Associate within our Private Banking Business Intelligence & Advanced Analytics team, you will help define and deliver data-driven analytics and GenAI solutions for J.P. Morgan Private Bank sales and marketing, strengthening decision-making, client engagement, and workflow efficiency.

Job Responsibilities 

• Drive stakeholder engagement across business, technology, and global teams to deliver high-impact data and analytics solutions.
• Align analytics and AI initiatives to evolving business strategies and measurable outcomes.
• Monitor industry trends and emerging methodologies to maximize the value of internal platforms and applications.
• Analyze client behavior, investment patterns, sales funnels, segmentation, and personas to generate actionable insights.
• Embed descriptive, diagnostic, predictive, and prescriptive analytics into business decisioning.
• Strengthen data models and feature stores while improving data quality and reuse.
• Implement ongoing model monitoring and performance measurement to support a data-driven culture.
• Develop analytical frameworks for marketing measurement, including A/B testing and campaign effectiveness.
• Model ROI, cost of acquisition, lifetime value, and attribution approaches (e.g., MMM and multi-touch attribution).
• Build ML-based prediction and recommendation solutions for propensity, opportunity sizing, wallet share, and personalization.
• Support GenAI/agentic AI solutions that enhance advisor and marketer workflows (e.g., content/audience building, insights, sentiment).

Required qualifications, capabilities and skills 

• Advanced quantitative degree (MBA or MS in Statistics, Math, Engineering, or related field) with Analytics/Data Science experience in Financial Services, Asset & Wealth Management, or Marketing.
• Proficiency in Python, PySpark, and SQL for large-scale data manipulation and analysis.
• Working experience with Pandas, NumPy, scikit-learn, and TensorFlow (or similar ML libraries).
• Experience with ML methods (regression/classification, clustering, SVMs, trees, neural nets).
• Expertise in ML techniques (feature engineering/selection, imputation, outlier handling, cross-validation, hyperparameter tuning, explainability).
• Excellent written and verbal communication skills, with the ability to translate findings into compelling narratives for diverse audiences.
• Demonstrated judgment, analytical rigor, curiosity, creativity, and critical thinking to simplify complex problems into actionable solutions.
• Ability to operate effectively in ambiguous, fast-evolving environments and adapt to shifting priorities and timelines.
• Strong time management and organizational skills with consistent delivery focus.
• Working knowledge of AWS and LLM/Foundation Model APIs (e.g., OpenAI, AWS Bedrock) to build GenAI solutions for synthesis, natural language querying, and conversational interfaces.
• Exposure to agentic AI, multi-step reasoning, RAG pipelines, and orchestration frameworks.