Data Scientist, Analytics & Modelling

Salary: $169,541 - 180,000 per year Requirements:

• We are looking for someone with expertise in data strategy, analytics, and modelling within a complex financial services environment.
• We need experience shaping and delivering data products for regulated, financial, operational, and analytical use cases.
• We expect strong knowledge of cloud-native data architecture and migration of legacy, on-premises systems to AWS services such as S3, Glue, and Redshift.
• We require hands-on ability with SQL, Python, and PySpark for data validation, quality assurance, and large-scale data processing.
• We value experience building Python-based data pipelines and utilities using tools such as Pandas, PySpark, and AWS Lambda.
• We are looking for someone who can establish and maintain metadata catalogs, data dictionaries, and data lineage documentation.
• We expect experience working in Agile environments and using tools such as Jira and Confluence to manage backlogs, user stories, and delivery milestones.
• We need someone who can collaborate effectively with business stakeholders and engineering teams, translating complex business needs into practical data solutions.
• We require the ability to communicate complex information clearly and influence stakeholders across functions.
• We expect applicants to be able to commute to New York, NY, with flexibility to travel to Wilmington, DE when needed.

• We will have you deliver strategic data initiatives across a large multinational bank, including cloud migration, platform modernization, and enterprise data transformation.
• You will define and execute product roadmaps for data assets supporting key financial, regulatory, operational, and analytical needs.
• You will design curated, reusable, and governed data products for Partnerships Card portfolios.
• You will act as the main connector between business stakeholders and engineering teams, gathering requirements and turning them into actionable product features.
• You will identify opportunities to create business value from data across Card Partnerships, Loans, Consumer Banking, and Credit Data.
• You will shape the design of data products using Partnerships Card knowledge and help guide roadmap decisions.
• You will architect and implement cloud-native data solutions to support migration from legacy storage to AWS.
• You will embed governance, lineage, metadata, and data quality standards throughout the delivery lifecycle.
• You will develop advanced data validation and quality assurance processes across TSYS data systems.
• You will ensure data integrity, consistency, and reliability across downstream banking platforms by detecting anomalies and resolving quality issues.
• You will build Python-based pipelines and utilities for ingestion, transformation, validation, and reconciliation of large credit datasets.
• You will create reusable code modules that support automated data operations and end-to-end data integrity.
• You will maintain metadata catalogs, data dictionaries, and lineage documentation to strengthen transparency and governance.
• You will facilitate and manage Agile processes, including prioritization, delivery tracking, backlog management, and milestone planning.
• You will produce documentation, reference materials, and training resources to help stakeholders use delivered data solutions effectively.
• You will also contribute to data science work by identifying data opportunities, building statistical and machine learning models, and developing predictive models to support decision-making.

• AWS
• Lambda
• Redshift
• Architect
• Cloud
• Confluence
• Support
• JIRA
• Machine Learning
• Python
• PySpark
• SQL
• pandas

More:

We are Barclays, working with hackajob to connect with exceptional professionals for this opportunity in New York, New York, with multiple positions available. The role is eligible for a base salary of $169,541 to $180,000 per year, with additional incentive eligibility through our Employee Referral Program. This position supports our broader enterprise data strategy, digital transformation, data monetization, and modernization efforts across the organisation. We expect colleagues to reflect our Values of Respect, Integrity, Service, Excellence, and Stewardship, and to work in line with our Barclays Mindset of Empower, Challenge, and Drive.

last updated 39 week of 2026