Executive Director - Data Scientist

• Define applied DS strategy and roadmap aligned to business priorities; identify, size, and prioritize use cases based on value, feasibility, and risk.
• Lead end-to-end ML lifecycle: problem framing, data assessment, feature engineering, model development, validation, deployment, monitoring, and iteration.
• Deliver production-grade solutions in close partnership with Engineering and Product, ensuring scalable architectures, reliability, and maintainability.
• Drive experimentation and measurement: establish A/B testing and causal inference approaches, define success metrics, and quantify business impact.
• Implement MLOps standards: CI/CD for ML, model registries, automated retraining, drift monitoring, and reproducible pipelines.
• Ensure responsible AI and governance: model risk management, explainability, bias/fairness, privacy, documentation, and audit readiness.
• Lead and grow a high-performing team: hiring, coaching, performance management, career development, and best-practice communities.
• Influence stakeholders and executive audiences: communicate tradeoffs, recommendations, and results clearly; drive alignment across functions.
• Establish DS operating mechanisms: intake processes, review boards (model/design), documentation standards, and delivery playbooks.
• Promote data-driven culture by enabling self-service analytics, raising data literacy, and strengthening decision frameworks.

You'll combine your years of proven development expertise with a never-ending quest to create innovative technology through solid engineering practices. Your passion and experience in one or more technology domains will help solve complex business problems to serve our Private Bank clients. As a constant learner and early adopter, you're already embracing leading-edge technologies and methodologies; your example encourages others to follow suit., * Bachelors or Master's degree in Computer Science, Statistics, Mathematics, Engineering, or related field and minimum 10 years of experience in data science/ML/analytics with 5+ years in leadership/management roles.

• Proven record delivering applied ML/AI solutions with measurable impact in production environments and strong foundation in statistics and ML (supervised/unsupervised learning, model evaluation, uncertainty, experimentation).
• Excellent stakeholder management skills; ability to translate business problems into DS solutions and influence decision and collaborate with firmwide ML teams, Business and Product Partners, peers in geographically dispersed teams, and colleagues across JPMorgan AWM's lines of business and functions to drive alignment, accelerate adoption of common AI capabilities, and deliver impactful solutions
• Ability to drive standards: documentation, code quality, reproducibility, review processes.
• Experience with GenAI/LLMs (prompting, RAG, evaluation, guardrails), or AI product delivery.
• Must have strong programming skills in Python, Go, or Java . ML/AI: classification/regression, tree-based models, NLP, time series, recommendation, anomaly detection (as applicable). Experimentation: A/B testing, causal inference, uplift modeling, metric design, statistical power.
• Ability to partner effectively with Data Engineers for data modeling, pipelines (batch/stream), feature stores. Expertise in MLOps & Production: model deployment patterns (batch/real-time), monitoring, drift detection, retraining, model registry, CI/CD for ML.

Preferred qualifications, capabilities and skills

• ML/AI: classification/regression, tree-based models, NLP, time series, recommendation, anomaly detection (as applicable).
• Experimentation: A/B testing, causal inference, uplift modeling, metric design, statistical power.
• Ability to partner effectively with Data Engineers for data modeling, pipelines (batch/stream), feature stores.
• Expertise in MLOps & Production: model deployment patterns (batch/real-time), monitoring, drift detection, retraining, model registry, CI/CD for ML.
• Cloud & Platforms: AWS and/or Azure (compute, storage, orchestration); containerization (Docker) and Kubernetes familiarity.
• Strong written and verbal communication; executive-ready narratives and crisp decision materials.

We offer a competitive total rewards package including base salary determined based on the role, experience, skill set and location. Those in eligible roles may receive commission-based pay and/or discretionary incentive compensation, paid in the form of cash and/or forfeitable equity, awarded in recognition of individual achievements and contributions. We also offer a range of benefits and programs to meet employee needs, based on eligibility. These benefits include comprehensive health care coverage, on-site health and wellness centers, a retirement savings plan, backup childcare, tuition reimbursement, mental health support, financial coaching and more. Additional details about total compensation and benefits will be provided during the hiring process.

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.