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@gayatrir
Data scientist driving production-ready ML, NLP, and scalable data engineering solutions.
I am a results-driven data scientist with deep experience building production ML and data engineering systems across fintech, edtech, and aerospace domains. I design end-to-end solutions—from automated ETL and feature engineering to model training, deployment, and monitoring—that deliver measurable business impact.
My work has improved customer retention, risk classification, and operational reliability: examples include a 25% lift in customer retention from churn models, 30% better risk segmentation in credit scoring, and 98%+ accuracy in fraud and fault detection systems. I blend classical statistics with modern deep learning and LLMs to solve classification, forecasting, recommendation, and anomaly-detection problems.
Technically, I deploy models and APIs at scale using Docker, FastAPI, Kubeflow, MLflow, SageMaker, Vertex AI, Kafka, and cloud platforms; I build pipelines with Spark, Airflow, dbt, and Snowflake; and I visualize and operationalize results in Tableau, Power BI, Streamlit, and Dash. I prioritize reproducibility, CI/CD, and observability in ML workflows.
I mentor junior data scientists, collaborate cross-functionally with product and compliance teams, and focus on delivering actionable insights that drive executive decision-making and operational improvements.
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Work history, roles, and key accomplishments
Krasaan Tech
Jan 2022 - Aug 2023 (1 year 7 months)
Developed credit risk and fraud detection ML models (XGBoost, LightGBM, SVM) improving risk segmentation by 30% and achieving 98% fraud detection accuracy; automated end-to-end ETL and streaming pipelines reducing latency by 60% and enabled real-time decisioning with Kafka and FastAPI.
Byju's
Apr 2019 - Jan 2022 (2 years 9 months)
Built predictive maintenance and recommendation systems using Random Forests and collaborative filtering, improving fleet/system reliability by 25% and reducing turnaround time by 15% while deploying scalable models on AWS SageMaker.
Innomatic's Research Labs
Sep 2017 - Apr 2019 (1 year 7 months)
Developed automated QA and defect-prediction models (Random Forest, Logistic Regression, SVM) that reduced manual search time by 80% and improved reporting turnaround; automated reporting and delivered dashboards to improve traceability.
Degrees, certifications, and relevant coursework
Master's in Computer Technology, Computer Technology
Master's in Computer Technology from Eastern Illinois University.
Software and tools used professionally
Apache Spark
ggplot2
GitHub
Bitbucket
Kubernetes
GitHub Actions
Bitbucket Pipelines
NumPy
Pandas
PySpark
Dask
dbt
MySQL
PostgreSQL
MongoDB
Hadoop
Gmail
Jira
Julia
TensorFlow
PyTorch
MLflow
scikit-learn
Keras
Kubeflow
Streamlit
Kafka
FastAPI
Trello
Gemini
Elasticsearch
AWS Lambda
Airflow
SQL
XGBoost
Hugging Face
LightGBM
LangChain
Polars
Pinecone
Monte Carlo
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