Data Scientist, Analytics and Modelling

hackajob is collaborating with Barclays to connect them with exceptional professionals for this role.

Barclays Bank Delaware seeks Data Scientist, Analytics and Modelling in New York, New York (multiple positions available).

What will you be doing?

• Deliver strategic data initiatives within a large multinational bank, including cloud migration, data platform modernization, and enterprise-wide data transformation programs.
• Define and execute product maps for data assets that support critical financial, regulatory, operational, and analytical use cases.
• Design curated, reusable, and governed data products on Partnerships Card portfolios.
• Use Agile methodology to deliver high impact-data solutions by serving as the primary bridge between business stakeholders and engineering teams gathering requirements, translating complex business requirements and technical limitations into actionable product features, and delivering scalable data solutions.
• Leverage data strategy expertise to unlock business value across key domains, including Card Partnerships, Loans, Consumer Banking, and Credit Data. Identify strategic opportunities to use data as an asset, influence roadmap decisions, and translate analytical insights into actionable outcomes that drive customer experience, revenue growth, and operational efficiency.
• Shape the design of data products using Partnerships Card expertise.
• Architect and implement cloud‑native data architecture knowledge to support the migration of legacy, on‑premises data storage systems to AWS, using cloud tools (e.g., S3, Glue, and Redshift).
• Embed data governance, lineage, metadata, and quality standards into every stage of the delivery lifecycle.
• Drive alignment with the bank’s enterprise data strategy by shaping initiatives around digital transformation, data monetization and modernization ensuring they integrate seamlessly with the broader business architecture and comply with evolving regulatory frameworks.
• Develop advanced data validation and quality assurance processes across TSYS data systems using SQL, Python, and PySpark.
• Ensure data integrity, consistency, and reliability across multiple downstream banking platforms by proactively identifying anomalies, resolving data quality issues, and maintaining trust in critical datasets.
• Design and implement Python‑based data pipelines and utilities to process large‑scale credit datasets including data ingestion, transformation, validation, and reconciliation using frameworks including Pandas, PySpark, and AWS Lambda.
• Develop reusable code modules that support automated data operations and maintain end‑to‑end data integrity across critical systems.
• Build and maintain metadata catalogs, data dictionaries, and data lineage documentation to support enterprise‑wide transparency and data governance initiatives.
• Facilitate and manage Agile processes to ensure clear prioritization, timely delivery and traceability of data features across cross‑functional teams. Champion Agile product management methodologies using tools such as Jira and Confluence to manage product backlogs, user stories, and delivery milestones.
• Enable knowledge transfer by creating documentation, reference materials, and training resources to support business stakeholders in effectively using delivered data solutions.
• Must be within commutable distance of New York, NY with flexibility to travel to Wilmington, DE. Occasional domestic travel to work from company’s DE office required.

Salary / Rate Minimum/yr: $169,541 per year

Salary / Rate Maximum/yr: $180,000 per year

The minimum and maximum salary/rate information above include only base salary or base hourly rate. It does not include any other type of compensation or benefits that may be available.

This position is eligible for incentives pursuant to Barclays Employee Referral Program.

To use innovative data analytics and machine learning techniques to extract valuable insights from the bank's data reserves, leveraging these insights to inform strategic decision-making, improve operational efficiency, and drive innovation across the organisation.

• Identification, collection, extraction of data from…