Data Analyst
Description
About The Company
Barclays is a leading global financial services provider with a rich history of innovation and commitment to delivering exceptional banking and financial solutions. With a strong presence across various markets, Barclays offers a wide range of services including retail banking, corporate banking, investment banking, and wealth management. The company prides itself on its customer-centric approach, leveraging advanced technology and data-driven strategies to meet the evolving needs of its clients. Barclays is dedicated to fostering a diverse and inclusive workplace, promoting sustainability, and maintaining the highest standards of integrity and excellence in all its operations.
About The Role
The purpose of this role is to enable data-driven strategic and operational decision-making within Barclays by extracting actionable insights from large and complex datasets. As a Data Analyst-AVP, you will be responsible for performing advanced analytics, developing predictive models, and creating visualizations that support regulatory compliance, risk management, and operational efficiency. This position requires a blend of technical expertise, analytical thinking, and collaborative skills to translate data into meaningful business insights. You will work closely with cross-functional teams to automate reporting processes, improve data quality, and enhance decision support systems, ensuring regulatory requirements are met with precision and timeliness.
Qualifications
The ideal candidate will possess a bachelor’s degree in Computer Science, Data Science, Statistics, or a related field. A master’s degree or higher is preferred. Extensive experience in data analysis, machine learning, and statistical modeling is essential. Proficiency in Python, SQL, and data visualization tools such as Tableau is required. Familiarity with data governance, regulatory reporting, and cloud-based data environments will be advantageous. Strong problem-solving skills, attention to detail, and the ability to communicate complex technical information effectively are critical. Candidates should demonstrate leadership qualities, strategic thinking, and the ability to work collaboratively in a fast-paced environment.
Responsibilities
- Develop, implement, and apply machine learning, AI, NLP, deep learning, and predictive analytics models to support regulatory insights, risk identification, and data quality trend analysis.
- Build, train, evaluate, and document models using Python and associated libraries such as pandas, NumPy, scikit-learn, and SpaCy.
- Integrate analytical models into reporting workflows, automation pipelines, and decision support tools, performing feature engineering as needed.
- Analyze existing reporting and operational processes to identify automation opportunities, enhancing efficiency and scalability.
- Automate manual processes using Python, VBA, Alteryx, and Microsoft Power Platform tools like Power Automate and PowerApps.
- Standardize processes to improve reliability, control effectiveness, and capacity management.
- Create interactive dashboards and visual reports using Tableau to facilitate stakeholder understanding and decision-making.
- Source, prepare, validate, and transform data for regulatory reporting, maintaining comprehensive documentation of data lineage, logic, and controls.
- Build automated, repeatable pipelines for regulatory reporting utilizing Python, SQL, and Tableau.
- Apply data governance best practices, including data quality controls, validation checks, and adherence to security and regulatory policies.
- Support audit and regulatory examinations through detailed documentation, methodology explanations, and evidence collection.
- Maintain and optimize database structures and queries supporting reporting and analytics across relational and cloud environments.
- Prepare technical documentation for data pipelines, models, and reporting processes.
- Conduct end-to-end testing, including validation, test planning, user acceptance testing, defect management, and deployment readiness.
Benefits
Barclays offers a comprehensive benefits package designed to support the health, well-being, and financial security of its employees. Eligible employees can access medical, dental, and vision coverage, as well as a 401(k) retirement plan with company contributions. The company provides life insurance, paid leave for various circumstances, and opportunities for professional development and career growth. Additionally, Barclays encourages work-life balance through flexible work arrangements and wellness programs. This position is also eligible for performance-based incentive awards, recognizing your contributions to the company's success.
Equal Opportunity
Barclays is committed to creating an inclusive environment where all employees are valued and respected. The company provides equal employment opportunities regardless of race, color, religion, gender, sexual orientation, gender identity, age, disability, or any other protected characteristic. Barclays believes that diversity fosters innovation and drives better decision-making, and actively promotes a culture of fairness, equity, and inclusion. All applicants and employees are encouraged to contribute their unique perspectives and talents to support the company's mission and values.
Skills
- AI
- Alteryx
- Analytics
- Automation
- Cloud
- Data Governance
- Data Lineage
- Data Pipelines
- Data Quality
- Data Science
- Data Visualization
- Deep Learning
- Feature Engineering
- Machine Learning
- NLP
- NumPy
- pandas
- Power Automate
- Power Platform
- Power Apps
- Predictive Analytics
- Python
- Regulatory Compliance
- scikit-learn
- spaCy
- SQL
- Statistics
- Tableau
- VBA