I am a Data Scientist (AI & ML Focus) with 5+ years building enterprise-scale ML systems in finance and consulting. I specialize in Generative AI (LLMs, RAG, LangChain), NLP, and deep learning, and I excel at bridging cutting-edge research with production deployment. I have delivered measurable business impact—80% faster response times, 40% fewer false positives, and 20% higher CTR—through robust ML platforms and explainable AI. I enjoy cross-functional collaboration and guiding AI strategy from proof-of-concept to scalable production while maintaining governance and compliance.…

Syamchand Chilaka

I am a Data Scientist (AI & ML Focus) with 5+ years building enterprise-scale ML systems in finance and consulting. I specialize in Generative AI (LLMs, RAG, LangChain), NLP, and deep learning, and I excel at bridging cutting-edge research with production deployment. I have delivered measurable business impact—80% faster response times, 40% fewer false positives, and 20% higher CTR—through robust ML platforms and explainable AI. I enjoy cross-functional collaboration and guiding AI strategy from proof-of-concept to scalable production while maintaining governance and compliance.…

Available to hire

I am a Data Scientist (AI & ML Focus) with 5+ years building enterprise-scale ML systems in finance and consulting. I specialize in Generative AI (LLMs, RAG, LangChain), NLP, and deep learning, and I excel at bridging cutting-edge research with production deployment.

I have delivered measurable business impact—80% faster response times, 40% fewer false positives, and 20% higher CTR—through robust ML platforms and explainable AI. I enjoy cross-functional collaboration and guiding AI strategy from proof-of-concept to scalable production while maintaining governance and compliance.

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Skills

Experience Level

Python
Expert
SQL
Expert
Power BI
Expert
TensorFlow
Expert
Tableau
Expert
R
Expert
PyTorch
Expert
AWS
Expert
Docker
Expert
Kubernetes
Expert
Java
Expert
Spark
Expert
Looker Studio
Expert
Keras
Expert
Azure
Expert
Scala
Expert
GitHub Copilot
Intermediate
Bash
Intermediate
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Language

English
Fluent

Work Experience

Data Scientist at CitiGroup
September 1, 2023 - Present
Led the development and deployment of a Generative AI chatbot using Hugging Face and LangChain, reducing customer response times by 80%. Built retriever-augmented generation pipelines with vector databases and feature engineering on financial text to improve document classification accuracy by 50%. Automated retraining and data preparation pipelines with MLflow and Airflow, cutting turnaround times by 20%. Designed production dashboards (Tableau and CloudWatch) to monitor model drift, latency, and uptime, and collaborated with compliance to embed explainability frameworks. Communicated strategy and results to C-suite, securing endorsement for AI infrastructure investments.
Data Scientist at Accenture
September 1, 2020 - July 1, 2022
Delivered a high-accuracy anomaly detection model (XGBoost) achieving 96% accuracy and deployed as an API microservice, reducing false positives by 40%. Built an NLP-based recommendation system with embeddings and feature engineering, elevating click-through rate by 20%. Automated ML workflows with AWS SageMaker and MLflow, and set up CI/CD pipelines in Jenkins for reproducibility. Leveraged Databricks (PyTorch + Spark) for distributed training, speeding up model training by 30%. Delivered real-time ML outputs via Power BI/Tableau dashboards; mentored junior data scientists on MLOps and feature engineering; led cross-functional AI working group to align ML roadmap with business priorities; produced audit-ready, explainability documentation.
Junior Data Scientist at Accenture
August 1, 2019 - August 1, 2020
Engineered predictive models (Decision Trees, Random Forests, XGBoost) achieving 72% accuracy in customer response prediction. Maintained SQL and Python ETL pipelines, reducing ML data prep time by 20%. Developed a CNN-based defect detection model deployed at the edge with 95% accuracy. Designed and executed A/B testing frameworks in Python, improving conversions by 20%. Supported cloud-native deployments on Azure using Docker and Kubernetes for production ML workloads.

Education

Master of Science in Computer and Information Science at Long Island University, Brooklyn, NY
January 11, 2030 - March 2, 2026
Bachelor of Technology in Computer Science at REVA University, Karnataka, India
January 11, 2030 - March 2, 2026
Master of Science in Computer and Information Science at Long Island University, Brooklyn, NY
January 11, 2030 - March 2, 2026
Bachelor of Technology in Computer Science at REVA University
January 11, 2030 - March 2, 2026

Qualifications

Add your qualifications or awards here.

Industry Experience

Financial Services, Professional Services
    paper Fraud Detection Project

    Just wrapped up a project I’m really proud of - a credit card fraud detection system with A/B testing built in.

    Here’s what I built:
    • Trained XGBoost, Random Forest, and Logistic Regression models on 284K+ transactions
    • Got the model to 98% ROC-AUC even though fraud cases were super rare (only 0.17% of data)
    • Built a REST API so it can make predictions in real-time
    • Added A/B testing so you can compare different models side-by-side in production
    • Made an interactive dashboard where you can upload files and see predictions instantly
    • Dockerized everything so it’s easy to deploy anywhere

    The hardest part was dealing with the massive class imbalance - had to use SMOTE and play around with class weights to get it working well. Also learned a ton about setting up proper A/B tests with 50/50 traffic splits and logging.

    Honestly pretty happy with how production-ready this turned out. It’s not just a notebook - it’s a full system you can actually deploy.

    Built with: Python, XGBoost, scikit-learn, FastAPI, Streamlit, Docker

    Code’s on GitHub: https://www.twine.net/signin