Phd Causal Inference Jobs Near Me

Join JPMorganChase’s Consumer Banking Customer Data & Analytics team as a Data Scientist Director supporting the American Dream Initiative, a firmwide, multi-year effort to expand economic opportunity in communities across the United States. This is an exciting opportunity to help shape a high-profile strategic initiative by developing advanced analytics that drive customer engagement, inform strategic decision-making, and measure progress toward expanding economic opportunity and financial well-being across the country. This is a senior leadership role that requires technical expertise, strategic vision, and executive-level influence to translate complex data into clear actionable decisions.

As a Data Scientist Director at JPMorganChase within the Consumer Banking Customer Data & Analytics team, you will build and lead a high‑performing team responsible for the end‑to‑end delivery of analytics solutions that support customer acquisition, engagement, servicing, and retention in support of the American Dream Initiative. You will define the analytics strategy, develop a high‑performing team, and partner closely with stakeholders across the firm to transform data‑driven insights into measurable business and community outcomes.

• Define and drive the customer analytics strategy for the American Dream Initiative, aligning measurement and prioritization to core goals.
• Build and lead a team to deliver high‑impact insights across the customer lifecycle, performance, and program effectiveness.
• Establish and oversee a performance measurement framework, including KPI development, executive reporting, experimentation, and impact assessment, to drive data‑informed decision‑making and program optimization.
• Partner with Product, Marketing, Research, and business stakeholders to develop data‑driven customer engagement strategies that improve acquisition, deepening, and retention.
• Leverage emerging AI, machine learning, and analytics capabilities to develop innovative solutions that enhance customer outcomes and advance the initiative’s goals.
• Translate complex analyses into clear narratives and recommendations for senior leaders, balancing strategic ambition with operational feasibility, risk discipline, and measurable outcomes.

• Master’s or PhD in a quantitative field and 10+ years of analytics experience.
• Proven senior leadership experience managing and developing multidisciplinary analytics teams in a large enterprise environment.
• Deep expertise in data science and analytics, including hands‑on experience with predictive modeling, statistical analysis, segmentation, and experimentation.
• Demonstrated ability to deliver AI, machine learning, and analytics solutions that drive measurable business outcomes, ideally within financial services or consumer products.
• Strong business acumen, with the ability to frame analytical problems in terms of business strategy and translate insights into executive‑level recommendations.
• Experience leading analytics across multiple concurrent business domains, balancing near‑term delivery with longer‑term capability building.
• Exceptional stakeholder management and communication skills, with a track record of influencing senior leaders and cross‑functional partners.
• Proficiency in Python and/or R, and experience with modern data platforms such as Snowflake or Databricks.
• Strong project and program management skills, including the ability to define success metrics, manage risks, and drive execution across complex initiatives.

• Consumer banking/financial services analytics across customer lifecycle, channels, marketing effectiveness, and servicing strategy
• Interest/experience in economic opportunity, community development, financial health, or social impact—using data to drive measurable outcomes
• Building KPI frameworks and multi‑channel attribution for initiatives balancing growth and customer impact objectives
• Hands‑on generative AI experience (LLMs, retrieval‑augmented generation, agentic AI frameworks)
• Causal inference and experimentation at scale (A/B testing, robust testing frameworks)
• Responsible AI knowledge: model governance and regulatory considerations in financial services
• Driving analytics adoption via change management, self‑service tooling, organizational enablement; familiarity with Agile/product practices