SANDEEP NAGULA

Handling data team of size 6 in which all the data related activities will be handled as mentioned below.

• Automation: Automation of all the types of data reports using Python.(which include daily,Weekly and monthly as per the requirement from our internal project stake holders
• Data Visualization-Dashboarding: Visualization of the data, which we receive from all our services like

104- call centre(Health Helpline)

MMU(Mobile medical units)

TMC(Tele medical units)

HWC(Health and wellness Centre)-LHF

Bahmni (Higher health facility)

Sakhi application(Asha related) etc.

In which 2 types of visualizations that include:

a)Visualization using Tableau.

b)Visualization using Open Source techniques using Python Dash and Streamlit which will be based on stake holder requirement.

Ref. Dashboard for 104 call centre for all the 4 locations which we serve.(which is created using Open Source Python Dash

http://hihl104.piramalswasthya.org:8090/

• Data Quality: Checking the quality of all the types of data which is coming to our AMRIT database by pre-processing the data using EDA techniques.
• Predictive Data Analytics: Based upon the type of data will we doing predictions and forecasting the same.

Some of them are mentioned below

a)Forecasting number of diseases based upon the historical data which we receive from our 104 call centres,MMU's,TMC data and all services and predicting top 10 diseases and their algorithm's using Time Series Forecasting. So that our services will run keeping predictive models data and act accordingly.

b) Prediction of NCD (Non Communicable Diseases) and

CD diseases based upon the data which we receive from the Sakhi Application (Asha App.) one of our service.

Like Prediction on Cancer /Hypertension Prediction /BP based upon the historical data and inputs provided by our Clinical domain team(Doctors) using Supervised Machine Learning techniques.

• Creation of Product related documents (PRD) necessary in creation of application by conducting workshop with Govt. and internal stake holders based upon the business requirements.

• Worked extensively with data pre-processing (data ingestion, data wrangling, data exploration, data manipulation) and machine learning techniques to infer marketing insights and forecast sales
• Responsible for using data visualization techniques to increase the usability and accessibility of data for the sales and marketing departments
• Developed dynamic reports, dashboards, and key performance indicators aligned with business strategies and initiatives •
• Develop dashboard and standardized reporting using Tableau that track operational performance in real-time with both aggregated and drill down functionality.
• Oversaw data management activities such as collection, cleansing, standardization, and mining.
• Used statistical techniques for hypothesis testing to validate data and interpretations

Projects Done:

Project Name: Industrial Clusters Identification http://tsocmms.nic.in/TLNPCB/userMaster/consent CTEDetail1B Project description: This project is intended to carry out to identify the different types of industries, their status, scale and all possible details. Synopsis: · Extract data from tsocmms. http://tsocmms.nic.in/TLNPCB/userMaster/getApp ValueForCTOTotalA?id=115852&days1=-1&a=z

· Performed data Exploration, Wrangling, Manipulation all possible Data Acquisition and EDA, Missing Values, cleaning and visualize data. · Build multiple models using different approaches i.e., supervised (Both Classification and Regression Models), Unsupervised models (K-Means Clustering) to gain insights from the data and to check the accuracy of the models.

·Visualizing the models using Matplotlib, Seaborn and Tableau.

Project Name: Market Strength Analysis https://www.mca.gov.in/mcafoportal/viewComp anyMasterData.do Project description: To find out the market potential of different segments and to gain insights from it.

Synopsis: ·

Collected data from MCA portal.

Pre-processed the data into required format.

Perform Feature engineering by different feature selection techniques.

Perform PCA, LDA and build models based on supervised learning

and visualizing.

Project Name: Industrial Segmentation https://tspcbbmwmanifest.cgg.gov.in/Reports/Vie wIndustries.aspx

Project description: To segment the industries based on their CFO

specifications and to gain insights from it. Synopsis: This Project is to segment the industries based their CFO in which Data is extracted,

Processed, building models and gaining insights from the Data to

identity the percentage of different segments in the market and

their capabilities.

Project Name: Healthcare - Survival rate-COVID-19 (Diabetes and Hypertension).

https://www.bharatbiotech.com/

Synopsis: Created an ML model to classify patient survival rate

with Covid19 affected having Diabetes and Hypertension by using

Supervised learning Classification models.

Project Name: Loan Eligible Prediction Synopsis:

Completed This project with Machine Learning Models.

• Worked with 1st Largest Indian MNC which is into Waste Management/Engineering/Pharma for their Customer Insights, Business Analytics and Development.
• Pre-Processing the data, Extensive Exploratory Data Analysis (EDA) & feature engineering. •
• Gathered, documented and modeled data to assess business trends.
• Evaluated consistency and importance of different business intelligence data against needs to determine optimal courses of action. •
• Synthesized current business intelligence data to produce reports and polished presentations, highlighting findings and recommending changes.

• Able to handle more than 60 students in a class.
• Conducted and participated in multiple cultural activates in college.
• Validated final engineering examination answer papers.

• Experienced in teaching Subjects like Neural Networks, Control Systems, Analysis of Linear Systems, Micro Processors and interfacing modeling of System components, Network Theory, Switching theory and Logic design.
• Able to handle more than 60 students in a class.
• Conducted and participated in multiple cultural activates in college.
• Validated final engineering examination answer papers.
• Controlled engineering activities to maintain work standards, adhere to timelines and meet quality assurance targets.