Analytics Solutions Senior Associate

hackajob is collaborating with J.P. Morgan to connect them with exceptional professionals for this role.

JOB DESCRIPTION

Are you a skilled data professional with a passion for transforming raw data into actionable insights and a proven track record of learning and implementing new technologies? The Finance Data & Insights Team is an agile product team responsible for the development, production, and transformation of financial data and reporting across Consumer and Community Banking (CCB). Our vision is to enhance the lives of our people and increase the firm's value by leveraging data and advanced tools to analyze information, generate insights, save time, improve processes and controls, and build future-ready skills. 

As an Analytical Solutions Senior Associate on the Finance Data & Insights Team, you will contribute to the design, delivery, and adoption of analytical solutions that convert financial data across multiple lines of business into actionable insights. You will partner with Finance stakeholders, Analytics peers, and Technology partners to translate business questions into well-controlled reporting, repeatable analysis, and scalable data pipelines. The role emphasizes hands-on development, strong execution, disciplined controls, and clear communication to accelerate time to insight and improve decision-making. 

Job Responsibilities 

Collaborate with Finance managers, product owners, and internal stakeholders to clarify business needs and translate them into well-defined analytical requirements, solution approaches, and delivery plans. 

Contribute to backlog refinement and sprint execution by breaking down work into actionable tasks, estimating effort, documenting assumptions, and delivering outputs with predictable quality and timelines. 

Create and maintain reporting, dashboards, data extracts, and lightweight tools that support decision-making, with a focus on standardization and reuse across similar use cases. 

Build and enhance reliable data pipelines by cleaning, modeling, and optimizing queries across large financial datasets, partnering with others to ensure solutions align with data standards and platform patterns. 

Automate manual work (for example, ad hoc queries, quality checks, and recurring reports) using tools such as Alteryx and Python , improving efficiency while maintaining auditability. 

Apply strong controls and documentation practices, including testing evidence, lineage awareness, reproducibility, and verified data and visualization accuracy consistent with evolving control requirements. 

Partner with Technology and platform teams to support operationalization of solutions, including deployment readiness, control alignment, and transition to steady-state support. 

Support enablement by producing clear documentation and participating in training and knowledge-sharing (including short how-to materials) to drive adoption and correct usage. 

Help measure adoption, user experience, and recurring pain points, and you will propose iterative improvements that reduce cycle time and improve stakeholder outcomes. 

Required Qualifications 

Bachelor's degree in MIS, Computer Science, Mathematics, Engineering, Statistics, Finance , or a related field. 

3+ years delivering analytical solutions, reporting, or data automation work, preferably in complex, regulated environments, with demonstrated ability to turn raw data into clear insights. 

Strong capability in business intelligence and data wrangling, including Tableau (advanced) and at least one of Alteryx, SAS, or Python for pipelines and Quality Control (QC) . 

Strong SQL skills across relational and/or big data systems, including the ability to build and optimize complex queries and large-scale summaries. 

Demonstrated experience developing reporting and conducting objective analysis using imperfect and/or disparate data sources, with attention to data quality and reconciliation. 

Ability to understand business context, ask effective questions, and communicate analytical findings clearly to both technical and non-technical audiences. 

Strong written and verbal communication skills, including the ability to document logic, assumptions, and controls in a way that supports review and reuse. 

A consistent focus on controls, risk management, and disciplined execution, with flexibility to adapt to evolving control requirements. 

Preferred Qualifications 

Prior experience in financial services (for example, banking, payments, or capital markets). 

Exposure to cloud and modern data platforms such as AWS, Databricks, or Snowflake , and big data query tools (for example, Hive , SQL , Python ). 

Familiarity with search-driven or self-service analytics tools (for example, ThoughtSpot ) and awareness of emerging capabilities such as AI-assisted insights. 

Experience automating ad hoc queries, building QC dashboards, and supporting operational reporting with defined controls and monitoring. 

Demonstrated product mindset, including contributing to roadmaps, supporting OKRs , tracking adoption signals, and proposing continuous improvements.