Data Scientist Lead

• Own the data quality posture of the Architecture Workbench, identifying gaps and improving completeness across architecture datasets
• Design automated data quality frameworks, including validation checks, scoring mechanisms, and exception reporting pipelines
• Collaborate with domain architects to remediate data issues and embed sustainable data governance practices
• Develop executive-grade dashboards and observability tools to monitor architecture data health and coverage
• Analyze architecture data to uncover trends, risks, and optimization opportunities within the technology estate
• Create recurring analytical products, including reports and visualizations, that address strategic and operational questions
• Track temporal changes in architecture to evaluate alignment with strategic direction and identify emerging deviations
• Translate complex analytical findings into clear narratives for senior technology and business stakeholders
• Identify critical unanswered architecture questions and build datasets and pipelines to address them systematically
• Apply AI and LLM techniques to automate discovery, classification, summarization, and insight generation
• Integrate disparate data sources into unified, queryable models enabling scalable and repeatable intelligence generation

Required qualifications, skills, and capabilities

• Strong hands-on experience with graph databases, particularly Neo4j — including Cypher query authorship, schema design, and graph analytics
• Expert proficiency in SQL and relational data modelling, with experience querying complex, multi-schema environments 
• Solid Python skills for data engineering, analysis, and pipeline development (pandas, SQLAlchemy, networkx, or equivalent)
• Demonstrable experience applying LLM and AI techniques to analytical or data problems — RAG pipelines, embedding-based search, prompt engineering, or similar
• Experience building data quality frameworks including automated validation, completeness scoring, and exception management
• Strong data visualisation skills — able to produce executive-grade analytical outputs using tools such as Plotly, Grafana, or custom-built dashboard.

• Experience working with firmwide enterprise data platforms, API-sourced data, and semi-structured or unstructured sources

  
  

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 for more information about requesting an accommodation.