Data Scientist Resume

1. JANAPATI SAI SUBRAHMANYAM
Associate Software Engineer
Phone: 9943633909, Email: janapati.saisubrahmanyam@gmail.com
Linkedin :- https://www.linkedin.com/in/sai-subrahmanyam-janapati
Blog :- https://knowledgengg.wordpress.com/
Kaggle :- https://www.kaggle.com/saisubrahmanyam/kernels
OBJECTIVE
To be involved in the type of work where I can utilize skill and creativity within the system, that effectively contributes to
the growth of organization.
EDUCATION | ACADEMIC QUALIFICATION
Examination University/School Location Year CGPA/Percent
B. Tech. Karunya University Coimbatore 2018 8.01
ECE
CERTIFICATIONS
• Post Graduation Program in Big Data Analytics and Optimization from INSOFE
• Introduction to Machine Learning by Andrue NG
• Intro to AI From Microsoft
• Python A-Z for DataScience by Kirill Ermakov.
SOFTWARE SKILLS
• Languages: Python, R, SQL, Java.
• DataScience Tools: Keras, SkLearn, Pandas, NumPy, Tableau, Dash, Plotly, ggPlot, NLTK, Spacy, Flask.
• BigData/Database Tools : PySPARK,Informatica, IBM Netezza.
• Operating Systems: Windows, Raspbian, Ubuntu.
DATASCIENCE PROJECTS
1. Benchmarking the error metrics of any structured data
• This application accepts any kind of structured data as input from a web based UI. It will do all the basic
Preprocessing in the backend, and will prompt the user to select the Machine learning and Deep Learning models
that he/she want to run their data benchmarking on.
• After this process user will be displayed with a Dashboards of all the error Metrics. These metrics can act as a
benchmark or a reference ones so that user can enhance or tune the models or data to improve the metrics.
• I have used Flask for web interactions, Sklearn for Machine learning,TensorFlow and Keras for Deep Learning,
Html and Css for Web UI.
2. Clinical Data Analysis on predicting Heart Stroke:
• Build a classification model for predicting the heart condition on various qualitative and quantitative measures.
3. Bankruptcy Prediction:
• This is an unbalanced data-set. Tried various techniques to deal the unbalance problem. Finally used XG-Boost
model and achieved a F1 score of 0.75 .
4. Sentiment analysis on IMDB Reviews:
• Build a Deep Learning LSTM model on the IMDB Review Corpus and achieved 87.59% Accuracy.
5. Adult Dataset:
• This dataset is about American census income classification. I have used various ML models and techniques on
this data, finally settled with CATBoost algorithm.

2. 6. Emnist data:
• Used CNN for identifying handwritten digits and alphabets.
IoT PROJECTS
• Solar car: (Dec 2016 - Mar 2017)
We have designed and developed a single seater car, powered by the solar cells. My role included the design and
integration of all on-board electronic sensors.
• Smart Streets: (Mar 2017 – July 2017)
Developed a Raspberry Pie based vehicle tracking and Street light control system for our college. This model will
track the vehicles that are entering the college premises and notify the guard if any unauthorized vehicle enters.
This process is done by validating the License Plate on the vehicle. I have used KNN for Character recognition.
CORPORATE EXPERIENCE
Accenture, Bangalore | May 2018 – till date
• Successfully automated the testing process that saved lot of time and resources.
• Successfully Analyzed the insurance data, that has to be reported to the government and build a Machine
Learning model to detect the errors in it before it is being reported by the Government (ISO). Which reduced the
reported error rate from 32% to 4%. This saved a lot of costs to the client.
• Build 5 dashboards to forecast the historical data loads such as financial, claims,etc.,This made the work of
Business Analyst a bit easier.
• Build 6 mappings in Informatica which have very minimal issues.
CO-CURRICULAR ACTIVITES
• Conducted a two-day workshop on developing multipurpose robot using Arduino, for our department’s annual
Technological Fest.
• Conducted a one-day Workshop on basics of Arduino.
• Participated in a National Level Conclave on IoT for Smart City.
AWARDS AND ACHIEVEMENTS
• Runner up in Machine Learning Hackathon conducted at INSOFE
• Winner in the Project Expo-2017 for the project Smart Streets
• Finalists in Electric Solar Vehicle Championship conducted by ISIE
• Runner up in the Pravega Aero carnival 2016, by IISC Bangalore.
RESEARCH INTEREST
• Machine Learning , Deep Learning and IoT.
PERSONAL INTEREST’S
• Reading blogs | playing badminton | computer games | Trying new things that makes my work simpler.