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I am Bala Santhoshi, a Data Scientist and AI/ML Engineer with 5+ years of experience designing, deploying, and optimizing scalable ML solutions across NLP, computer vision, and advanced analytics. I specialize in building robust supervised and unsupervised models using algorithms like Logistic Regression, Random Forest, XGBoost, and SVM, and I fine-tune architectures such as CNNs, LSTMs, Transformers, and large language models (BERT, GPT, LLaMA) with TensorFlow, PyTorch, and Hugging Face. I excel in Python programming, data engineering, feature engineering, and data visualization, and I have hands-on experience deploying production-grade AI systems on AWS and Azure, with Docker, Kubernetes, and MLOps practices. Across my roles at Capital One and Zensar Technologies, I have led end-to-end ML lifecycles, built NLP tools and predictive models, and delivered scalable inference pipelines and explainable AI reports that drive business outcomes and ensure regulatory compliance.…I am Bala Santhoshi, a Data Scientist and AI/ML Engineer with 5+ years of experience designing, deploying, and optimizing scalable ML solutions across NLP, computer vision, and advanced analytics. I specialize in building robust supervised and unsupervised models using algorithms like Logistic Regression, Random Forest, XGBoost, and SVM, and I fine-tune architectures such as CNNs, LSTMs, Transformers, and large language models (BERT, GPT, LLaMA) with TensorFlow, PyTorch, and Hugging Face. I excel in Python programming, data engineering, feature engineering, and data visualization, and I have hands-on experience deploying production-grade AI systems on AWS and Azure, with Docker, Kubernetes, and MLOps practices. Across my roles at Capital One and Zensar Technologies, I have led end-to-end ML lifecycles, built NLP tools and predictive models, and delivered scalable inference pipelines and explainable AI reports that drive business outcomes and ensure regulatory compliance.

Bala Santhoshi

Data Scientist, AI Engineer, Cloud Developer, +2

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I am Bala Santhoshi, a Data Scientist and AI/ML Engineer with 5+ years of experience designing, deploying, and optimizing scalable ML solutions across NLP, computer vision, and advanced analytics. I specialize in building robust supervised and unsupervised models using algorithms like Logistic Regression, Random Forest, XGBoost, and SVM, and I fine-tune architectures such as CNNs, LSTMs, Transformers, and large language models (BERT, GPT, LLaMA) with TensorFlow, PyTorch, and Hugging Face. I excel in Python programming, data engineering, feature engineering, and data visualization, and I have hands-on experience deploying production-grade AI systems on AWS and Azure, with Docker, Kubernetes, and MLOps practices. Across my roles at Capital One and Zensar Technologies, I have led end-to-end ML lifecycles, built NLP tools and predictive models, and delivered scalable inference pipelines and explainable AI reports that drive business outcomes and ensure regulatory compliance.…I am Bala Santhoshi, a Data Scientist and AI/ML Engineer with 5+ years of experience designing, deploying, and optimizing scalable ML solutions across NLP, computer vision, and advanced analytics. I specialize in building robust supervised and unsupervised models using algorithms like Logistic Regression, Random Forest, XGBoost, and SVM, and I fine-tune architectures such as CNNs, LSTMs, Transformers, and large language models (BERT, GPT, LLaMA) with TensorFlow, PyTorch, and Hugging Face. I excel in Python programming, data engineering, feature engineering, and data visualization, and I have hands-on experience deploying production-grade AI systems on AWS and Azure, with Docker, Kubernetes, and MLOps practices. Across my roles at Capital One and Zensar Technologies, I have led end-to-end ML lifecycles, built NLP tools and predictive models, and delivered scalable inference pipelines and explainable AI reports that drive business outcomes and ensure regulatory compliance.

Available to hire

I am Bala Santhoshi, a Data Scientist and AI/ML Engineer with 5+ years of experience designing, deploying, and optimizing scalable ML solutions across NLP, computer vision, and advanced analytics. I specialize in building robust supervised and unsupervised models using algorithms like Logistic Regression, Random Forest, XGBoost, and SVM, and I fine-tune architectures such as CNNs, LSTMs, Transformers, and large language models (BERT, GPT, LLaMA) with TensorFlow, PyTorch, and Hugging Face. I excel in Python programming, data engineering, feature engineering, and data visualization, and I have hands-on experience deploying production-grade AI systems on AWS and Azure, with Docker, Kubernetes, and MLOps practices.

Across my roles at Capital One and Zensar Technologies, I have led end-to-end ML lifecycles, built NLP tools and predictive models, and delivered scalable inference pipelines and explainable AI reports that drive business outcomes and ensure regulatory compliance.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Language

Javanese

Advanced

Afar

Advanced

English

Fluent

Work Experience

AI/ML Engineer at Capital One Financial

May 1, 2024 - Present

Designed and deployed transformer models with Hugging Face and PyTorch to analyze trading data streams, reducing anomaly detection latency and safeguarding billions of dollars in financial transactions processed monthly with high accuracy. Developed GPT-powered NLP tools automating complex financial document analysis and regulatory compliance checks, cutting manual review time by weeks while processing thousands of diverse documents during each audit cycle. Engineered advanced feature extraction pipelines combining time-series indicators, market sentiment scores, and macroeconomic datasets, significantly improving risk prediction models by optimizing runtimes from hours to minutes on massive financial datasets. Built and maintained scalable ML workflows on AWS Lambda, S3, and SageMaker, automating continuous model retraining and batch inference for credit risk scoring models processing more than 10 terabytes of data every month reliably. Collaborated with quantitative researchers and c

Data Scientist at Zensar Technologies

July 1, 2023 - September 5, 2025

Constructed and deployed time-series forecasting models using LSTM and XGBoost in TensorFlow and PyTorch, increasing asset price prediction accuracy by 22% and improving trading strategies and portfolio returns. Built NLP pipelines with BERT transformers using Hugging Face and Keras for real-time financial news and social media sentiment analysis, enhancing trading precision by 18% while processing over 10,000 data points daily. Established scalable, cloud-native ML workflows leveraging AWS SageMaker with automated retraining and batch inference, reducing model update latency by 50% and cutting infrastructure costs by $120K annually. Implemented unsupervised anomaly detection models using autoencoders and isolation forests to reduce false positives by 30% and detect 200+ fraudulent transactions monthly. Engineered end-to-end CI/CD pipelines using Docker, Kubernetes, and GitHub Actions to automate testing, validation, and deployment, shortening deployment cycles by 40%. Conducted featur

AI/ML Engineer at Capital One Financial

May 1, 2024 - Present

Designed and deployed transformer models with Hugging Face and PyTorch to analyze trading data streams, reducing anomaly detection latency by over 30 seconds and safeguarding billions of dollars in monthly transactions processed. Developed GPT-powered NLP tools automating complex financial document analysis and regulatory compliance checks. Engineered advanced feature extraction pipelines combining time-series indicators, market sentiment scores, and macroeconomic datasets, improving risk prediction runtimes from hours to minutes. Built and maintained scalable ML workflows on AWS Lambda, S3, and SageMaker, automating continuous model retraining and batch inference for credit risk scoring. Collaborated on explainable AI reports to streamline regulatory audits. Integrated multiple data sources into ensemble models, boosting prediction accuracy for market-moving events. Architected RESTful APIs to deploy GPT-powered chatbots for analysts, reducing report generation time. Optimized end-to-

Data Scientist at Zensar Technologies

July 1, 2023 - September 5, 2025

Constructed time-series forecasting models using LSTM and XGBoost in TensorFlow and PyTorch, increasing asset price prediction accuracy and enhancing trading strategies. Developed real-time NLP pipelines with BERT and Hugging Face for financial news sentiment analysis. Established cloud-native ML workflows with AWS SageMaker, automating model retraining and batch inference while maintaining 99.9% uptime. Implemented unsupervised anomaly detection using autoencoders and isolation forests, reducing false positives and detecting fraudulent activity. Built end-to-end CI/CD pipelines (Docker, Kubernetes, GitHub Actions) to accelerate deployment and reduce costs. Performed feature engineering on large financial datasets and built dashboards with Tableau, supporting data-driven decision-making. Adapted traditional ML models to healthcare datasets and deployed risk stratification models on AWS SageMaker, integrating outputs with clinical KPIs in Tableau.