Data Analyst Scientist

Monika Nanjappa

+1-346-***-**** ******.***********@*****.*** linkedin.com/in/monika-nanjappa-8639b8222

Profile Summary

Results-driven AI & Data Analyst, Data Scientist with 5+ years of experience designing and delivering end-to-end analytics and machine learning solutions across energy, utilities, and public sector domains. Proven track record in building predictive models using Python, SQL, and cloud platforms (AWS, Azure) to drive data-driven decisions. Experienced in integrating SAP EAM and SAP SD data with advanced analytics workflows to uncover asset lifecycle trends and optimize operations. I specialized in developing anomaly detection systems, NLP pipelines, and fine-tuning large language models (LLMs) for unstructured data analysis. Skilled in automating data pipelines, crafting explainable ML solutions, and leveraging deep learning architectures for classification, forecasting, and decision. Adept at translating complex data into actionable insights and collaborating in Agile teams to scale AI solutions from prototype to production.

Education

Master of Science in Data Science (GPA -4) (Statistics, Data Analysis, SQL, GEN AI, ML, Data Mining, Snowflake, Python,R)

University of Houston

Bachelors of Engineering in Computer Science (GPA -4)

Sir M Visveswaraya Institute of Technology

Experience

DATA ANALYST & DATA SCIENTIST, BP PLC (2019–2024)

Integrated data from Azure, AWS, and SAP ECC and S/4 HANA systems to support real-time analytics for asset management and performance monitoring. Built predictive machine learning models using Python to identify equipment anomalies across NOV, HMH, and Cameron rigs, reducing downtime risk and improving operational reliability. Used SQL Server and DAX to design dashboards that visualized equipment health and financial KPIs, which guided decision-making across global teams. Automated ERP reporting pipelines through AI-enhanced chatbot workflows, increasing data accessibility and accelerating response times for stakeholders.

DATA ANALYST & AI SPECIALIST, HARRIS COUNTY PROPERTY & TAX DIVISION (2025–Present)

Led data initiatives to automate the property tax e-filing process by integrating SQL Server with Tyler API, streamlining data flow and reducing manual intervention. Designed and implemented fuzzy matching logic using Python and SQL to resolve naming inconsistencies in Comptroller datasets, significantly improving data integrity for downstream reporting. Developed scalable duplicate detection and validation procedures using SQL stored procedures, ensuring clean, audit ready datasets. These efforts laid the foundation for reliable and accurate Tableau visualizations used in compliance and financial reporting.

Skills Implementation

Created executive dashboards using Tableau that pulled SAP SD and Azure data to track KPIs like order-to-cash metrics and pricing trends, helping BP’s finance team reduce monthly reporting time by nearly 40%.

Built SQL pipelines to prepare and clean large property tax datasets for Tableau reporting, ensuring timely and accurate visuals that supported filing accuracy at Harris County.

Designed reusable dashboard components with filters, parameters, and calculated metrics that allowed Harris County’s business users to explore data independently, reducing their reliance on ad hoc reports.

Automated the end-to-end property tax e-filing workflow by integrating SQL Server with Tyler API, making the data directly consumable in Tableau dashboards and improving transparency in high-volume submissions.

Developed anomaly detection dashboards in Tableau using data from SAP SD and asset logs at BP, giving operations teams a real-time view of inconsistencies and improving reaction times.

Optimized slow-running dashboards by restructuring SQL queries, exposure to Hive and Spark for querying large-scale datasets in distributed environments and pre-aggregating data for visual layers, which improved performance during peak usage across both BP and Harris County dashboards.

Created a fuzzy matching model using Python and SQL to detect and resolve phonetic mismatches in taxpayer names. The cleaned dataset powered audit-friendly Tableau dashboards with over 95% matching accuracy.

Worked closely with teams in finance, operations, and compliance to define dashboard metrics and logic. These sessions ensured the Tableau dashboards aligned with business goals and regulatory requirements.

Built a geospatial ML model using SAP SD and operational data to predict high-potential gas exploration areas. The results were turned into interactive Tableau maps for BP’s exploration team to evaluate site viability.

Developed automated procedures in SQL to generate dynamic serial numbers and map cross-linked records, which made Tableau reporting for Harris County’s financial systems more accurate and consistent.

In the Blowout Preventer (BOP) reliability project, built and deployed an anomaly detection model using Python and integrated its output into Tableau. This helped BP reduce unplanned offshore equipment downtime by 22%.

Developed credit card analytics dashboards with segment-level breakdowns (education, income, job type) supporting customer segmentation, behavior analysis, and loyalty insights. Delivered dashboard walkthroughs to business teams, communicating revenue drivers and user trends across job types, age groups, and spending categories

Documented the logic behind KPI calculations, joins, and filters within Tableau dashboards to support maintainability and transparency for future analysts and auditors.

Built dashboards to monitor property tax filing success and errors using SQL-driven inputs and Tableau visualizations, enabling faster correction cycles at Harris County.

Helped restructure data models from SAP SD and Oracle systems to integrate better with Tableau, which improved data refresh success rates and enabled more stable reporting pipelines.

Developed automated Power BI executive dashboards combining SAP SD data and Azure cloud analytics, providing daily financial insights and reducing monthly reporting cycle times by 40%and wrote complex DAX functions.

Skills

Tableau dashboard development, Jira, Git, SQL querying and optimization, data modeling, performance tuning and dashboard optimization, calculated fields and parameters in Tableau, Python for data processing, ETL and data pipeline development, anomaly detection and data validation, SAP EAM and SAP SD data integration, AWS and Azure cloud platforms, Python, R, cross-functional collaboration, technical documentation, user-centric dashboard design, Agile project execution, Pyspark, kafka, Bigdata.

REFERENCES

CLYDE LEUCHTAG (Deputy Division Director) - *****.********@**************.***

CLAUDIA TORRES (Administrative Supervisor)- *******.******@**************.***

JACKIE NGUYEN (Database Administrator & Technical Support)- ******.******@**************.***

NANDA GOPAL ( CFO & CIO ) - **********.*****@*********.***

TEJASWINI MARIGOWDA (Director) - *********@**********.***

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