NLP Data Analysis for Amex

Speech-to-Text Annotation and Quality Monitoring for Banking Services

Overview

Contributing to American Express (Amex) Speech-to-Text annotation project at ObjectWays Technologies, focusing on processing French customer service interactions to improve machine learning accuracy and banking service quality monitoring.

Project Scope

Amex SST Annotation Project

Processing and analyzing customer service transcripts for:

  • Machine Learning model training
  • Quality assurance monitoring
  • Service improvement insights
  • Compliance verification

Technical Responsibilities

1. Data Processing

Speech-to-Text Transcript Cleaning:

  • Process French CCP (Customer Care Personnel) interactions
  • Clean CM (Card Member) conversation transcripts
  • Standardize transcript formats
  • Remove noise and artifacts

Data Preprocessing:

  • Text normalization
  • Error correction
  • Annotation tagging
  • Quality validation

2. Large-Scale Analytics

BigQuery SQL:

  • Complex query development
  • Large dataset analysis
  • Performance optimization
  • Data aggregation and reporting

ETL Processing:

  • Apache Beam: Distributed data processing
  • Dataform: SQL-based data transformation
  • Cloud Data Fusion: Visual ETL pipeline design
  • Pipeline orchestration and scheduling

3. NLP & Machine Learning

Advanced Tools:

  • vTensorAct Studio: NLP annotation platform
  • Amazon SageMaker: ML model training and deployment
  • Encord: Data annotation and management

Quality Monitoring:

  • Achieve 90% accuracy in interaction monitoring
  • NLP-based sentiment analysis
  • Key phrase extraction
  • Compliance checking

4. LiDAR Data Annotation

Autonomous Vehicle Applications:

  • Object detection annotation
  • 3D point cloud labeling
  • Ground truth data generation
  • Quality assurance

Technical Stack

Cloud & Data Platforms

  • Google Cloud Platform (GCP)
  • BigQuery for data warehousing
  • Cloud Data Fusion for ETL

Programming & Tools

  • SQL (Advanced)
  • Python for data processing
  • NLP libraries and frameworks

Annotation Platforms

  • vTensorAct Studio
  • Amazon SageMaker
  • Encord

Key Achievements

Accuracy Metrics

  • 90% accuracy in quality monitoring
  • Improved ML model training data quality
  • Enhanced customer service insights
  • Reduced manual review time

Process Improvements

  • Streamlined annotation workflows
  • Automated quality checks
  • Efficient data pipeline design
  • Scalable processing architecture

Language Expertise

French Language Processing

  • Native French speaker advantage
  • Cultural context understanding
  • Nuanced conversation interpretation
  • Industry-specific terminology

Business Impact

For Banking Services

  • Improved customer satisfaction monitoring
  • Better service quality metrics
  • Compliance verification
  • Staff performance insights

For Machine Learning

  • High-quality training data
  • Reduced model bias
  • Improved prediction accuracy
  • Faster model iteration

Project Challenges

1. Language Complexity

Challenge: French linguistic nuances
Solution: Native speaker expertise and context analysis

2. Scale

Challenge: Processing millions of interactions
Solution: Distributed processing with Apache Beam

3. Accuracy Requirements

Challenge: Banking industry quality standards
Solution: Multi-stage validation and quality checks

4. Real-time Processing

Challenge: Timely data availability
Solution: Optimized ETL pipelines and caching

Skills Demonstrated

  • Data Engineering: ETL, BigQuery, Apache Beam
  • NLP: Text processing, annotation, analysis
  • Cloud Computing: GCP services and architecture
  • Quality Assurance: Validation and testing
  • Domain Expertise: Banking and financial services
  • Language Skills: Professional French proficiency

Technologies Used

  • BigQuery SQL
  • Apache Beam
  • Dataform
  • Cloud Data Fusion
  • vTensorAct Studio
  • Amazon SageMaker
  • Encord
  • Python
  • NLP tools and libraries

Employment Details

Company: ObjectWays Technologies
Location: Chennai, Tamil Nadu, India (Remote)
Role: Data Analyst
Period: November 2024 - Present
Employment Type: Full-time Remote

Professional Growth

  • Large-scale data processing expertise
  • Banking domain knowledge
  • Advanced NLP techniques
  • Cloud platform proficiency
  • Cross-functional collaboration
  • Quality-focused mindset

Future Applications

The skills and experience gained from this project are directly applicable to:

  • PhD research in NLP and ML
  • Large-scale data analytics
  • Financial technology (FinTech)
  • Quality assurance systems
  • Automated monitoring solutions