Data Analyst
Description
About The Company
Barclays is a leading global financial services provider with a rich history of innovation and excellence. Renowned for its commitment to delivering exceptional banking and financial solutions, Barclays operates in numerous countries, serving millions of customers worldwide. The company emphasizes integrity, customer focus, and sustainable growth, fostering a dynamic environment where talented professionals can thrive. With a strong emphasis on technological advancement and data-driven decision-making, Barclays continually invests in innovative solutions to meet evolving client needs and regulatory requirements.
About The Role
The purpose of this role is to enable data-driven strategic and operational decision-making through the extraction of actionable insights from large datasets. As a Data Analyst-AVP, you will be responsible for performing statistical and advanced analytics to uncover trends and patterns, translating these insights into clear visualizations and comprehensive reports. You will play a crucial role in supporting regulatory compliance, risk management, and operational efficiency by developing, implementing, and maintaining complex data models and automated reporting pipelines. This position offers an exciting opportunity to influence decision-making at a senior level within Barclays, leveraging cutting-edge technologies such as machine learning, artificial intelligence, and natural language processing.
Qualifications
The ideal candidate will possess a bachelor’s degree in Computer Science, Data Science, Statistics, or a related field; a master’s degree is preferred. Extensive experience with Python and analytical libraries such as pandas, NumPy, scikit-learn, and SpaCy is essential. Proficiency in SQL, Tableau, and data visualization tools is required, along with a strong understanding of data governance, data quality, and regulatory compliance standards. Candidates should demonstrate prior experience in building automated data pipelines, developing predictive models, and integrating these models into operational workflows. Strong problem-solving skills, excellent communication abilities, and a proven track record of leading analytical projects in a financial or regulated environment are highly desirable.
Responsibilities
- Develop, implement, and apply machine learning, AI, NLP, deep learning, and predictive analytics models to support regulatory insights, data quality trend analysis, and risk identification.
- Build, train, evaluate, and document models using Python and relevant analytical libraries, ensuring robustness and accuracy.
- Integrate models into reporting workflows, automation pipelines, or decision support tools, performing feature engineering to optimize model performance.
- Analyze current reporting and operational processes to identify opportunities for automation, efficiency gains, and process improvements.
- Replace manual steps with end-to-end automated workflows utilizing Python, VBA, Alteryx, and Microsoft Power Platform (Power Automate/PowerApps).
- Standardize processes to improve scalability, capacity, reliability, and control effectiveness across reporting functions.
- Create interactive dashboards and visualizations using Tableau to facilitate data interpretation and decision-making.
- Source, prepare, validate, and transform data for regulatory reporting, maintaining logic, lineage, and documentation in compliance with internal controls and external regulations.
- Build automated, repeatable regulatory reporting pipelines leveraging Python, SQL, and Tableau.
- Apply data governance practices, including data quality controls, validation checks, metadata management, and adherence to policies ensuring data integrity, security, and accessibility.
- Support audit and regulatory examinations through comprehensive documentation, methodology explanations, and responses to compliance inquiries.
- Maintain and optimize database structures and queries supporting regulatory reporting and analytics in relational and cloud environments.
- Prepare detailed technical documentation for data pipelines, models, workflows, and analytical processes.
- Conduct end-to-end testing, including validation of requirements, test planning, execution, user acceptance testing (UAT), defect management, and deployment readiness.
Benefits
Barclays offers a comprehensive suite of employee benefits designed to support the well-being and professional growth of its team members. Eligible employees can access medical, dental, and vision coverage, along with a competitive 401(k) retirement plan. The company also provides life insurance, paid leave for various circumstances, and opportunities for continuous learning and development. This position is also eligible for an incentive award, recognizing outstanding performance and contributions. Barclays fosters a collaborative and inclusive environment, emphasizing work-life balance and employee engagement.
Equal Opportunity
Barclays is committed to creating a diverse and inclusive workplace. We are an equal opportunity employer and do not discriminate based on race, color, religion, gender, sexual orientation, gender identity or expression, age, disability, or any other protected characteristic. We believe that diverse perspectives foster innovation and drive better outcomes for our clients and communities. All qualified candidates will be considered for employment without regard to any protected status, and we encourage individuals from all backgrounds to apply.
Skills
- Accessibility
- AI
- Alteryx
- Analytics
- Automation
- Cloud
- Data Governance
- Data Pipelines
- Data Quality
- Data Science
- Data Visualization
- Deep Learning
- Feature Engineering
- Machine Learning
- Metadata Management
- NLP
- NumPy
- pandas
- Power Automate
- Power Platform
- Power Apps
- Predictive Analytics
- Python
- Regulatory Compliance
- scikit-learn
- spaCy
- SQL
- Statistics
- Tableau
- VBA