Raghu Ram Vadali - Telco Customer Churn Prediction

Q: Where is Raghu Ram based?

Raghu Ram is based in Munich, Germany .

Q: What languages does Raghu Ram speak?

Raghu Ram speaks the following languages: Hindi (Native), Telugu (Native), English (Advanced), German (Intermediate) .

Q: How many years of experience does Raghu Ram have?

Raghu Ram has at least 15 years of experience. During this time, Raghu Ram has worked in at least 6 different roles and for 4 different companies . The average length of individual experience is 3 years and 7 months . Note that Raghu Ram may not have shared all experience and actually has more experience.

Q: What is Raghu Ram's latest experience?

Raghu Ram's most recent position is Telco Customer Churn Prediction – End-to-End ML Pipeline at Self-Initiated Project .

Q: What companies has Raghu Ram worked for in recent years?

In recent years, Raghu Ram has worked for Self-Initiated Project and ARRK Engineering .

Q: Which industries is Raghu Ram most experienced in?

Raghu Ram is most experienced in industries like Automotive , Food and Beverage , and Information Technology (IT) . Raghu Ram also has some experience in Telecommunication and Banking and Finance .

Q: Which business areas is Raghu Ram most experienced in?

Raghu Ram is most experienced in business areas like Product Development , Project Management , and Research and Development (R&D) . Raghu Ram also has some experience in Business Intelligence , Information Technology (IT) , and Finance .

Q: Which industries has Raghu Ram worked in recently?

Raghu Ram has recently worked in industries like Automotive , Food and Beverage , and Information Technology (IT) .

Q: Which business areas has Raghu Ram worked in recently?

Raghu Ram has recently worked in business areas like Product Development , Project Management , and Research and Development (R&D) .

Recommended expert

Munich, Germany

Experience

Jul 2025 - Jul 2025

1 month

Telco Customer Churn Prediction – End-to-End ML Pipeline

Self-Initiated Project

Designed and implemented a full machine learning pipeline for churn prediction using the Telco dataset.
Applied preprocessing techniques including missing value handling, categorical encoding, feature scaling, and PCA.
Built and compared over 15 models (logistic regression, random forest, XGBoost, etc.) and evaluated them using accuracy, precision, recall, F1 score, ROC AUC, and PR AUC.
Tuned hyperparameters with GridSearchCV, achieving 80.6% accuracy with random forest and XGBoost.
Created visual reports (bar plots, heatmaps, radar charts) to interpret model performance and churn drivers.
Exported reusable pipelines and trained models with joblib for deployment.

Mar 2025 - Mar 2025

1 month

Stock Price Analysis and Risk Modeling

Self-Initiated Project

Analyzed historical stock data from Yahoo Finance using adjusted closing prices.
Computed simple and exponential moving averages to identify market trends.
Evaluated performance via daily and cumulative returns.
Visualized correlation heatmaps and kernel density estimation (KDE) plots.
Assessed value at risk (VaR) at 95% and 99% confidence using variance-covariance, historical simulation, and Monte Carlo simulation with over 10,000 trials.
Calculated Sharpe ratio and volatility metrics to evaluate risk-adjusted returns.

Jan 2025 - Dec 2025

1 year

Food101 Multiclass Image Classification – Progressive Learning with TensorFlow (EfficientNetV2S)

Self-Initiated Project

Implemented multiclass image classification on Food101 dataset using a progressive learning strategy.
Prepared progressive datasets (10%, 50%, 100%) to enable staged model training using image_dataset_from_directory.
Built an input pipeline with 384×384 image size, batch loading, and data augmentation.
Applied EfficientNetV2S pretrained on ImageNet with hybrid pooling (GlobalAverage + Max pooling) and dropout before output.
Phase 1 (10% data): Feature extraction with frozen layers achieving 52% accuracy (15% validation).
Phase 2 (50% data): Fine-tuned last 30 layers with label smoothing achieving 80% accuracy (25% validation), improved to 83.5% with extended epochs.
Phase 3 (100% data): Fine-tuned last 30 layers with learning rate of 1e-5 achieving 83.5% accuracy (25% validation).
Achieved top-1 accuracy of 83.15% and top-5 accuracy of 96.59%.
Computed precision, recall, F1-score, and support per class.
Plotted per-class F1 score distribution and heatmaps of precision, recall, and F1.
Analyzed precision versus recall trade-offs and generated a correlation matrix of evaluation metrics.
Performed misclassification analysis to identify classes with highest errors, including top 10 misclassified categories and confusion patterns.

Feb 2015 - Present

11 years 2 months

Munich, Germany

Simulation Engineer / Project Leader

ARRK Engineering

Led crash simulations and airbag performance studies; developed predictive models with LS-Dyna and Pam-Crash.
Delivered engineering insights and recommendations to cross-functional teams and clients.

Oct 2012 - Feb 2015

2 years 5 months

Munich, Germany

CAE Specialist / Project Leader

Tecosim GmbH

Built and validated crash models.
Applied statistical methods and sensitivity studies to optimize safety performance.

Sep 2008 - Aug 2010

2 years

Chennai, India

Senior Engineer (Crash Analyst)

Renault-Nissan

Analyzed full-vehicle crash simulations.
Conducted parametric studies to improve crashworthiness.

Industries Experience

See where this freelancer has spent most of their professional time. Longer bars indicate deeper hands-on experience, while shorter ones reflect targeted or project-based work.

Experienced in Automotive (15.5 years), Food and Beverage (1 year), and Information Technology (1 year).

Automotive

Food and Beverage

Information Technology

Business Areas Experience

The graph below provides a cumulative view of the freelancer's experience across multiple business areas, calculated from completed and active engagements. It highlights the areas where the freelancer has most frequently contributed to planning, execution, and delivery of business outcomes.

Experienced in Product Development (15.5 years), Project Management (13.5 years), and Research and Development (3.5 years).

Product Development

Project Management

Research and Development

Summary

Mechanical Engineer with 14+ years of experience in Finite Element Analysis (FEA), simulation modeling, and predictive analytics, now transitioning into AI, Machine Learning, and Deep Learning. Skilled in Python, TensorFlow, and Scikit-learn to design and train neural networks (ANN, CNN, RNN/LSTM) for regression, classification, image recognition, and time series forecasting. Completed self-initiated projects in computer vision (Food101 classification, EfficientNetV2S transfer learning), customer churn prediction, and stock risk modeling, showcasing expertise in end-to-end ML pipelines, optimization techniques, and model evaluation.

Skills

Programming Languages And Data: Python, C, Mysql.
Development Tools: Jupyter Notebook, Git, Pycharm, Vs Code.
Data Analysis And Visualization: Pandas, Numpy, Scikit-learn, Matplotlib, Seaborn.
Machine Learning: Regression, Classification, Clustering, Model Evaluation & Validation, Feature Engineering, Xgboost.
Deep Learning (Tensorflow/keras) - Ann & Cnn: Regression, Classification, Image Classification, Feature Extraction, Transfer Learning: Pretrained Models (Efficientnetv2s, Imagenet).
Deep Learning (Tensorflow/keras) - Optimization: Dropout, Weight Decay, Lr Scheduling, Label Smoothing.
Deep Learning (Tensorflow/keras) - Sequence & Time Series: Rnn, Lstm, Gru, Sliding Window Forecasting.
Deep Learning (Tensorflow/keras) - Model Evaluation: Precision, Recall, F1, Roc, Misclassification Analysis.
Mechanical Engineering: Cad, Fea (Ls-dyna, Pam-crash, Abaqus), Matlab.

Languages

Hindi

Native

Telugu

Native

English

Advanced

German

Intermediate

Education

Oct 2010 - Sep 2012

University of Stuttgart

Master of Science, Computational Mechanics of Materials and Structures · Computational Mechanics of Materials and Structures · Stuttgart, Germany

Oct 2000 - Jun 2004

Jawaharlal Nehru Technical University

Bachelor of Engineering, Mechanical Engineering · Mechanical Engineering · India

Certifications & licenses

Data Science Bootcamp

Udemy

Machine Learning A-Z: AI, Python

Udemy

Python For Data Analysis And Visualization

Udemy

TensorFlow For Deep Learning Bootcamp

Udemy

MySQL For Data Analytics & BI

Udemy

Profile

Created

December 2025

Last Update

December 2025

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Frequently asked questions

Do you have questions? Here you can find further information.

Where is Raghu Ram based?

Raghu Ram is based in Munich, Germany.

What languages does Raghu Ram speak?

Raghu Ram speaks the following languages: Hindi (Native), Telugu (Native), English (Advanced), German (Intermediate).

How many years of experience does Raghu Ram have?

Raghu Ram has at least 15 years of experience. During this time, Raghu Ram has worked in at least 6 different roles and for 4 different companies. The average length of individual experience is 3 years and 7 months. Note that Raghu Ram may not have shared all experience and actually has more experience.

What roles would Raghu Ram be best suited for?

Based on recent experience, Raghu Ram would be well-suited for roles such as: Telco Customer Churn Prediction – End-to-End ML Pipeline, Stock Price Analysis and Risk Modeling, Food101 Multiclass Image Classification – Progressive Learning with TensorFlow (EfficientNetV2S).

What is Raghu Ram's latest experience?

Raghu Ram's most recent position is Telco Customer Churn Prediction – End-to-End ML Pipeline at Self-Initiated Project.

What companies has Raghu Ram worked for in recent years?

In recent years, Raghu Ram has worked for Self-Initiated Project and ARRK Engineering.

Which industries is Raghu Ram most experienced in?

Raghu Ram is most experienced in industries like Automotive, Food and Beverage, and Information Technology (IT). Raghu Ram also has some experience in Telecommunication and Banking and Finance.

Which business areas is Raghu Ram most experienced in?

Raghu Ram is most experienced in business areas like Product Development, Project Management, and Research and Development (R&D). Raghu Ram also has some experience in Business Intelligence, Information Technology (IT), and Finance.

Which industries has Raghu Ram worked in recently?

Raghu Ram has recently worked in industries like Automotive, Food and Beverage, and Information Technology (IT).

Which business areas has Raghu Ram worked in recently?

Raghu Ram has recently worked in business areas like Product Development, Project Management, and Research and Development (R&D).

What is Raghu Ram's education?

Raghu Ram holds a Master in Computational Mechanics of Materials and Structures from University of Stuttgart and a Bachelor in Mechanical Engineering from Jawaharlal Nehru Technical University.

Does Raghu Ram have any certificates?

Raghu Ram has 5 certificates. Among them, these include: Data Science Bootcamp, Machine Learning A-Z: AI, Python, and Python For Data Analysis And Visualization.

What is the availability of Raghu Ram?

Raghu Ram is immediately available full-time for suitable projects.

What is the rate of Raghu Ram?

Raghu Ram's rate depends on the specific project requirements. Please use the Meet button on the profile to schedule a meeting and discuss the details.