Data Analyst Project Management

ANINDITA AGUAN

Email: ***.*****@*****.***, Phone: 669-***-****

Location: San Jose, CA, LinkedIn

PROFESSIONAL SUMMARY

Energetic, goal-oriented certified Data Analyst/Business Data Analyst well versed with Agile Scrum and Waterfall methodologies with over 10 years of experience in banking sector.

Good understanding of various Project Management tasks related to preparing Project Plan, Project Estimates, Schedules, Resource Planning and Project related Status Reports.

Strong background in data extraction, transformation, and analysis using SQL Server, Teradata and Apache Spark and Python ensuring accurate and actionable insights.

Experience in implementing system requirements by defining and analyzing application problems after conducting requirement gathering sessions with various business stakeholders employing proper elicitation techniques such as JAD, Discovery, Story boarding, Brainstorming, workshops, questionnaire, surveys, and focus group etc.

Provided support to Product Owner in sprint planning, daily stand-ups, reviews, retrospectives, release planning, demos, and other Scrum-related meetings.

Expertise in creating Epics, features, User stories, flow charts, tasks for product backlogs and prioritizing User Stories.

Experience in developing solutions by preparing and evaluating alternate workflows solutions and conducting various analysis viz. Requirements, GAP, Risk, Feasibility, and Impact analysis.

Skilled in building interactive dashboards and reports in Tableau, Power BI and Excel to track key performance metrics, campaign effectiveness, and compliance trends.

Proficient in data mapping and integration, aligning disparate CRM data (Salesforce, MS Dynamics) with enterprise data warehouses to enhance reporting accuracy.

Hands-on experience in data validation, cleansing, and applying business rules, ensuring high data quality for analytics and compliance reporting.

Experience working with ETL tools (Informatica) and cloud platforms (Azure) to streamline data workflows and automate reporting solutions.

Experienced in Salesforce data modeling, creating custom objects and fields, and designing validation rules to improve data quality and accuracy for reporting and analysis.

Collaborated with cross-functional teams to optimize marketing campaigns, enhance customer segmentation, and improve compliance monitoring using data-driven insights.

Assisted in developing Test Scenarios and test cases, experience with UAT Testing (UAT planning, testing, scheduling, and analysis), Train-the-trainer sessions, user manuals and sign-off documents.

Experienced in managing the postproduction support incidents and tickets using tools like ServiceNow and Atlassian Jira Align.

Excellent communication skills and a good team player with analytical and problem-solving skills with proven ability to deliver within stringent deadlines.

TECHNICAL SKILLS:

Project Management Tools

MS Project, Monday.com

Requirement Gathering Tools

JIRA, HP-ALM

UML tools

MS Visio, Adobe Spark, Draw.io

Modelling/Prototype Tools

Balsamiq, Invision, Justinmind

Databases and Data Warehouse

Oracle, MySQL, SQL Server, Teradata, Apache Spark

Data Visualization Tools

Tableau, Power BI, Excel

Languages and Tools

SQL, Python, SAS, Google Analytics

Big Data & Cloud Technologies

Apache Spark, Azure

Other Applications

SharePoint,Confluence,MSOffice Suite 365,Salesforce, MS Dynamics

EDUCATION DETAILS:

Dual Degree (Bachelor of Technology and Master of Technology) in Ocean Engineering & Naval Architecture from Indian Institute of Technology Kharagpur, India in July 2014.

OTHER PROFESSIONAL QUALIFICATIONS & CERTIFICATION:

Oracle Database SQL Certified Associate (Oracle University)

Oracle PL/ SQL Developer Certified Associate (Oracle University)

Oracle Certified Java SE8 Programmer 1 (Oracle University)

IIBA Entry Certificate in Business Analysis (ECBA)

Certified Professional Scrum Master I

PROFESSIONAL EXPERIENCE:

Bank of America, Piscataway, NJ

Business Data Analyst, July 2024 – Present

In this project, the focus is on optimizing marketing campaigns by leveraging data-driven insights to improve customer targeting, enhance conversion rates, and maximize return on investment. The role involves using Apache Spark for large-scale data processing, SQL for data extraction and transformation, and Tableau for visualizing campaign performance.. This project also requires close collaboration with business stakeholders to align marketing strategies with organizational goals and enhance overall campaign effectiveness.

Responsibilities:

Conducted requirement gathering sessions with marketing and business teams to define campaign objectives and segmentation, managed user stories and backlog in JIRA, actively participating in Agile ceremonies to drive campaign optimization.

Designed and documented data flow diagrams, process workflows, and data mapping specifications to ensure seamless integration of marketing data across systems.

Utilized SQL and Apache Spark to extract, transform, and analyze large-scale customer and investment product data from enterprise data lakes, enabling data-driven marketing decisions and campaign optimization.

Conducted gap analysis to identify discrepancies between campaign objectives and actual performance, leveraging insights from SQL-based data analysis.

Optimized SQL queries to improve campaign data processing efficiency, reducing execution time and enhancing report generation speed.

Created Tableau dashboards to visualize key marketing performance indicators (KPIs), customer engagement trends, and conversion rates.

Conducted trend analysis on customer engagement metrics, identifying key drivers of successful campaigns and providing actionable insights to marketing teams.

Defined business rules for campaign segmentation, ensuring accurate data-driven targeting based on historical transaction patterns and customer behaviors.

Leveraged AI-powered predictive modeling to enhance customer segmentation and campaign targeting, increasing engagement and conversion rates.

Supported API based data integration between marketing platforms and internal systems to streamline campaign tracking and investment product performance analysis.

Conducted A/B testing and performance analysis, leveraging SQL and Apache Spark to refine campaign strategies and maximize conversion rates.

Assisted in User Acceptance Testing (UAT) for campaign performance dashboards and data pipelines, ensuring alignment with business objectives.

Leveraged Generative AI models to generate personalized marketing content based on customer investment behaviors and past interactions, improving engagement and conversion rates.

Analyzed transaction patterns and portfolio allocations to optimize marketing campaigns for high-net-worth clients, ensuring personalized investment recommendations.

Supported the implementation of ETL processes to enhance data accuracy and streamline reporting across multiple marketing initiatives.

Collaborated with cross-functional teams (marketing, IT, compliance) to implement automation and process improvements, reducing manual efforts and enhancing efficiency.

Wells Fargo, San Francisco, CA

Senior Data Analyst/Business Analyst, May 2022 – April 2024

The project was regarding implementation of Data Quality rules and conformance of different CRM data of commercial banking for building KPI metrics as a part of Data Governance initiatives. This helped in identification and proactive remediation of defective data which increased data accuracy in critical metrics significantly. Development of KPI metrics dashboards enhanced business decision making on bank’s performance and incentive compensation of relationship managers.

Responsibilities:

Collaborated with business stakeholders to define reporting requirements and deliver data-driven insights focused on loan portfolio performance and customer segmentation.

Gathered and documented business requirements in close collaboration with business and IT teams to ensure data solutions met business objectives.

Developed and optimized Tableau dashboards to visualize key business metrics, including loan performance, customer engagement, and financial trends, enabling data-driven decision-making.

Ensured data accuracy and consistency by applying data quality rules to loan and customer datasets, conducting data validation and cleaning processes.

Worked closely with the tech team to design and implement ETL Informatica workflows for extracting, transforming, and loading large datasets into data warehouses.

Mapped data from different CRMs (Salesforce, MS Dynamics) to conform to the data warehouse schema, ensuring consistency and data integrity.

Utilized SQL for complex queries and data manipulation to support reporting and analysis of loan and customer data.

Applied Python to automate data extraction, cleaning, and transformation tasks, ensuring the accuracy and consistency of the data.

Performed data modeling for data warehouse design, structuring and organizing data to support business analysis and reporting needs.

Prepared detailed reports using Excel and Tableau, providing stakeholders with insights into loan and customer data performance.

Automated routine reporting tasks and ensured efficient, real-time reporting through Python scripts and ETL workflows.

Collaborated with Salesforce administrators and developers to implement custom fields, workflows, and validation rules to enhance data quality and ensure alignment with business requirements.

Led the requirements gathering and documentation for Salesforce data migration and integration efforts, ensuring seamless transition of customer data with minimal disruption to business operations.

Conducted User Acceptance Testing (UAT) to validate those reports, dashboards, and data tools met user requirements and business standards.

Delivered regular updates and presentations to key stakeholders, showcasing data analysis results and providing actionable insights for business optimization.

Conducted root cause analysis and presented findings to business units to improve operational processes and performance.

Ensured data governance, quality, and compliance with banking regulations during all stages of data processing and reporting.

Banner Bank, Walla Walla, WA

Business Data Analyst, April 2021 – April 2022

The project included enhancing Know Your Customer (KYC) and Anti-Money Laundering (AML) processes by incorporating Lexis Nexis for customer verification and risk assessment. This involved leveraging SQL, Tableau, and Python to deliver data-driven insights that supported compliance monitoring and reporting. The project focused on designing robust data pipelines, validating data quality, and creating dashboards to provide real-time monitoring of KYC and AML activities, ensuring alignment with regulatory standards.

Responsibilities:

Integrated Lexis Nexis data to enhance customer verification, identify high-risk individuals, and improve AML investigations.

Conducted thorough data analysis to identify potential compliance risks and flagged accounts requiring further investigation, ensuring alignment with AML regulations.

Utilized Python and SQL to automate data enrichment processes and streamline integration of Lexis Nexis data into the KYC and AML systems.

Collaborated with the tech team to design ETL workflows in Informatica, ensuring seamless extraction, transformation, and loading of KYC and AML-related data into the data warehouse.

Collaborated on integrating Lexis Nexis APIs for KYC and AML checks by testing and mapping data shared through Java SPI connections to ensure smooth and accurate data flow.

Integrated the chatbot with LexisNexis and internal databases to provide real-time risk assessment insights.

Developed data quality rules and validation checks to ensure the accuracy of KYC and AML datasets, focusing on consistency across various data sources.

Ensured data from various systems, including Lexis Nexis, CRM, and transaction databases, was properly mapped and aligned with the data warehouse schema.

Supported AML monitoring efforts by analyzing transactional data, identifying suspicious patterns, and preparing reports on compliance status.

Created dynamic Tableau dashboards to provide real-time visibility into KYC verification and AML case progress, enabling compliance teams to take proactive actions.

Delivered insightful reports to senior management using Excel, highlighting trends, potential risks, and key performance metrics related to AML activities.

Gathered requirements from business, compliance, and IT teams to ensure data solutions met regulatory standards and business objectives.

Conducted User Acceptance Testing (UAT) on newly developed AML and KYC reports, dashboards, and automated data pipelines, ensuring they met business and compliance requirements.

Collaborated with UX designers to align business requirements with user interface design for AML/KYC workflows, ensuring a seamless and intuitive user experience across digital banking platforms.

Ensured that all data processing related to KYC and AML adhered to internal governance policies and external regulatory requirements.

Indian Bank, India

Financial Data Analyst, July 2016 – Jan 2021

Worked in the bank’s financial analytics team in order to streamline data collection processes, improve customer data quality, integrate data visualization tools to improve reporting efficiency and provide actionable suggestions after in depth marketing data analysis to optimize marketing campaigns, improve marketing strategies and increase sales and customer loyalty.

Responsibilities:

Constructed data consistency checks and automated error correction, improving data quality.

Partnered with the banking product team to analyze user behavior data and identify opportunities for product feature improvements. that increased user engagement.

Monitored, tracked, and reported on financial market trends and other related information

Analyzed market trends, financial statements, and other data to identify potential investment opportunities.

Automated financial report generation using Tableau, saving the zonal branches approximately 10 hours per week in manual data entry.

Identified potential risk within business processes and compliance violations and communicate them to stakeholders through concise dashboards and reports.

Performed SQL and Python-based analysis to analyze customer transaction records and buying patterns, enabling precision targeting and boosting campaign response rates.

Analyzed customer interactions with the bank’s online platforms using Google Analytics, identifying trends and user behaviors to enhance user experience and optimize digital marketing efforts.

Assisted in the PLM process by tracking loan and savings product lifecycles, managing metadata, and maintaining data accuracy across systems.

Coordinated with cross-functional teams to support CRM and PLM data mapping during Salesforce migration.

Utilized data analysis techniques to create models that forecast the success of marketing campaigns by identifying patterns and trends within historical campaign data, allowing for proactive optimization and better targeting of future efforts.

Conducted an in-depth data governance review that enforced compliance with regulatory standards, minimizing risk and avoiding potential fines.

Conducted ad-hoc analyses to uncover operational inefficiencies, resulting in the realignment of resource allocation that decreased operational costs.

Collaborated with IT department to design a bespoke analytics dashboard for real-time performance metrics, improving stakeholder reporting capabilities.

HSBC, India

Marketing Data Analyst, Sept 2014 – July 2016

Being part of the campaign management team for North America region, was involved in identifying new customer segments and changes to marketing using financial and behavioral analysis that led to designing better campaign strategies and enhanced marketing campaign performance.

Responsibilities:

Collaborated in market research initiatives that unveiled new customer segments, resulting in sales increase.

Used Microsoft Power BI for dynamic data visualization, which helped marketing team to understand customer trends more quickly.

Utilized SAS to analyze and predict customer behavior data, identify segments leading to a targeted marketing campaign and increasing cross-sell rates.

Developed predictive

Created comprehensive reports and dashboards to communicate marketing performance metrics to stakeholders improving data driven decision making.

Implemented a real-time dashboard using Microsoft Power BI, fostering data-driven decision-making across all marketing campaigns.

Conducted A/B testing to evaluate the effectiveness of 30+ marketing campaigns and recommend improvements in product feature and marketing strategies.

Developed predictive models and designed campaign strategies based on regression analysis identifying key attributes to increase traffic and conversions.

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