---
title: "Nitish Manikanta Bysani - Skin Disorder Prediction | Data Scientist | Predictive Modeling | Machine Learning | Python in Hyderabad | Tal"
description: "Meet Nitish Manikanta Bysani, | Data Scientist |Python | SQL | Power BI | Machine Learning | Deep Learning | Gen AI based in Hyderabad. AI stack includes gemini, hugging face, and langchain."
image: "https://tal.club/meet/nitish-manikanta-bysani/share-image"
---

# Nitish Manikanta Bysani on Tal

## Headline

\| Data Scientist \|Python \| SQL \| Power BI \| Machine Learning \| Deep Learning \| Gen AI

## About

Data Scientist with 3\.1 years of experience in building end\-to\-end machine learning and data\-driven solutions across analytics, forecasting, and intelligent automation use cases\. Skilled in Python, SQL, and advanced statistical techniques with hands\-on experience in classification, clustering, and deep learning models using Scikit\-learn, PyTorch, and TensorFlow\. Experienced in designing scalable ML pipelines on Azure and AWS, including data ingestion, feature engineering, model evaluation, and monitoring\. Recently focused on Generative AI and LLM\-based applications, implementing Retrieval\-Augmented Generation \(RAG\) systems, prompt engineering, vector search, and model evaluation workflows using GPT\-4, Claude, and LangChain\. Strong in translating business requirements into analytical solutions, delivering production\-ready ML systems with a structured and problem\-solving mindset\.

## Location

Hyderabad

## AI stack

gemini

hugging face

langchain

openai

## Work experience

Skin Disorder Prediction \| Data Scientist \| Predictive Modeling \| Machine Learning \| Python at Full\-time, Jan 2023 \- Dec 2023 · 1 yr, Hyderabad, Telangana, India, 1\. Collected and pre\-processed skin image datasets, including resizing, normalization, and augmentation\. 2\. Performed exploratory data analysis to understand class distribution and data imbalance\. 3\. Built and trained deep learning models using CNN architectures for multi\-class image classification\. 4\. Applied transfer learning techniques to improve model performance and reduce training time\. 5\. Evaluated model performance using accuracy, precision, recall, F1\-score, and confusion matrix\. 6\. Tuned hyperparameters to optimize model accuracy and reduce overfitting\. 7\. Collaborated with stakeholders to understand clinical requirements and ensure model interpretability\. 8\. Assisted in deploying the trained model as a web\-based application for real\-time prediction\.

## Education

Postgraduate Degree, Business analytics, Heriot\-Watt University

Bachelor of Commerce \- BCom, Computer Applications in Commerce, Keshav Memorial Institute of Commerce and Sciences \(KMICS\)

[View the original profile](https://tal.club/meet/nitish-manikanta-bysani)

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