Senior Reporting and Automation Analyst - Python and Generative AI

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We are seeking an experienced and strategic Senior Analyst for our Reporting Insights and GenAI Team. The ideal candidate will be responsible for driving the development and implementation of analytical solutions to support key business objectives for Legal Analytics as part of COO (Chief Operating Office). This role requires a strong analyst with a proven track record of delivering impactful insights and fostering a data-driven culture.
Roles and Responsibilities:
The Reporting Insights and GenAI Senior Analyst (Legal Analytics) accomplishes results by contributing significantly to the bank's success by focusing on improving efficiency, accuracy, and insights through data and process optimization. The responsibilities involve a blend of data analysis, report generation, and the development of automated solutions.
Data Collection and Analysis: Gathering data from various sources, cleaning it, and analyzing it to identify trends, patterns, and insights relevant to business operations.
MIS and Reporting: Designing, developing, and maintaining regular and ad-hoc Management Information Systems (MIS) and reports for different stakeholders. These reports often present key performance indicators (KPIs), operational metrics, and financial data in an understandable format.
Automation Development: Identifying manual, repetitive tasks and processes within the organization and developing automated solutions to streamline them. This can involve scripting, using automation tools/technologies like SQL, SAS, Python, PySpark, Tableau etc.
Process Improvement: Analyzing existing workflows to pinpoint inefficiencies and recommend improvements, often leveraging automation to achieve these.
Dashboard Creation: Developing interactive dashboards using reporting tools (e.g., Tableau, Python, Power BI) to provide real-time visibility into performance and trends.
Applied AI and GenAI Integration: Leading the exploration, development, and integration of Artificial Intelligence (AI), Machine Learning (ML), and Generative AI (GenAI) solutions. This includes leveraging Large Language Models (LLMs), Natural Language Processing (NLP), and predictive analytics to enhance data-driven decision-making and automate complex analytical processes.
Stakeholder Communication: Presenting findings and recommendations to various departments and management, explaining complex data in a clear and concise manner.
System Maintenance: Ensuring the accuracy and reliability of reporting systems and automation tools, troubleshooting issues, and performing regular updates.
Documentation: Responsible for documenting data requirements, data collection / processing / cleaning, and exploratory data analysis, which may include Process Automation / Optimization and data visualization techniques.
Data Governance and Quality: Contributing to efforts to maintain data quality, consistency, and adherence to data governance policies.
Data Handling: Work with large, complex and unstructured data to evaluate, recommend, and support the implementation of business strategies
Core Competencies:
Data Analysis & Insight Extraction: Proficiently applying analytical techniques to complex datasets to fetch meaningful, actionable insights that address business questions and drive decision.
Data Manipulation & Querying: Expert ability to query and manipulate data from various data sources (using SQL/Python/R), ensuring data quality and readiness for analysis and reporting.
Reporting & Visualization Tools: Expertise in using reporting & visualization platforms (e.g., Tableau, Power BI, Qlik Sense, MicroStrategy) to design, develop, and maintain dynamic dashboards and reports that clearly communicate performance and insights. This includes a strong focus on MIS and executive-level reporting.
Automation Technologies & Scripting: Strong capability in identifying automation opportunities, developing and implementing automated solutions using automation tools and scripting languages, and optimizing existing automated workflows.
Applied AI/ML and GenAI: Strong understanding and practical application of machine learning concepts, predictive modeling, and Generative AI technologies, including prompt engineering and experience with LLMs, to solve business problems.
Problem-Solving: Proactively identifying issues and developing practical, value-driven solutions.
Qualifications:
5+ years of experience in Reporting & Automation, Reporting Insights and GenAI with proficiency in business intelligence tools/technologies like SQL, SAS, Python, Tableau, MicroStrategy, etc.
Ability to develop scripts for automating routine tasks (e.g., Python scripting for file processing, API integrations).
Experience demonstrating a strong track record in developing reports, performing data analysis, and implementing automation solutions.
Strong understanding of the reporting and automation data & analytics ecosystem; ability to establish a scalable analytics framework – data strategy, process optimization, actionable insights, visualization techniques.
Demonstrable experience in developing and deploying AI/ML models (e.g., for forecasting, classification, NLP) or GenAI-powered applications in a business or financial context.
Hands-on experience with AI/ML frameworks and libraries (e.g., Scikit-learn, TensorFlow, PyTorch) and familiarity with prompt engineering techniques for Large Language Models (LLMs).
Experience with any banking operations (e.g., expense analytics, movement of funds, cash flow management, fraud analytics, ROI). Knowledge of regulatory requirements related to data privacy and security.
Education:
Bachelors/University degree in STEM, Master’s degree preferred
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Job Family Group: Decision Management
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Job Family:Data/Information Management
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Time Type:Full time
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