Chanakya Daparthy

Major milestones achieved:

• Utilized advanced querying, visualization and analytics tools to analyze and process complex data sets
• Hired, built and mentored a high inspirational team with collaborating culture and high impact problem solving, managed a mixed team of Machine Learning engineers, Finance and Marketing analysts by demonstrating the value of data driven reporting, problem solving, and impact to reduce churn by 10% and increase revenue by 20%
• Spearheaded end to end initiatives to align IT systems with business needs utilizing data analysis and synthesis, process mapping and stakeholder management, which enabled better decision-making and improved efficiency integrating sales and marketing data
• Acted as a liaison between business stakeholders and the Data team by consistently building high efficient, impactful data models and performance dashboards, resulting in a 30% increase in client satisfaction using SQL & SAS E-Miner
• Created and executed A/B testing and MVT (Multivariate) Testing plans by working closely with the product team, stakeholders and Data engineers Designed and implemented significance testing methods
• Expert in using multiple data sources - Finding the right KPIs and improving KPIs for different processes - from product Finance, Manufacturing to end Retail.
• Exemplified marketing and financial strategy support systems based on various Regression, ensemble models, Marketing mix models, process optimization, Time series modeling for finance and consumer models to predict demand
• Dynamic forecasting (time series) for production with retail demand
• As a Hands -on Data Scientist, for the product manufacturing process, developed Key Performance Indicators (KPIs) that helped to improve on-time delivery of products to the Retail Store by 21% while reducing cost by 7% in 2 years
• Based on the KPIs, built a team to generate key reports using Power BI Using various Regression, ensemble models, Marketing mix models, process optimization, and Time series modeling using python, SAS & SQL

• Developed a product based on risk stratification model for population health
• Developed a high impactful predictive model and association rules for predicting a Crisis event of 18-21 year old during child to adult Transition using claims data
• Developed a hospital readmission risk model for mental health & SUD patients within 30 days of discharge based on analysis of patient condition, treatment, and other factors. The model resulted in a 3% reduction in hospital readmission's and a net savings of $395,000
• Developed and implemented a predictive model for hospital re-admissions in mental health and substance abuse population implementing machine learning techniques in python and SAS
• Created active dashboards with linked visualizations in Tableau
• Developed and implemented a vendor risk model, using Random forest and XGboost ML algorithms to analyse and predict key behaviors including credit, on-time supply & quality
• Tools used : SQL, SAS, Tableau & Python,Tensorflow

• Collected data and developed statistical models using Python and applied machine learning algorithms to analyze and interpret the data
• Helped Data Scientist Dr Lixia Yao on Healthcare data for patent analytics- on unstructured data
• Data cleansing and mining the healthcare patent data for terms specified by UMLS on Hadoop cluster using map reduce using python, R and visualizations using D3.js
• Developed innovation strategies for medical device industry by data mining and analyzing patents of particular companies using Hadoop- hive, map reduce & Python.

• Helped Microsoft in building data base and analytics application using python Business requirement analysis and functional technical document preparation & Lead a team of 6 engineers in Developing and testing web application UI including C# & SQL Server
• Conducted functional, integration, regression, and performance testing to ensure software quality and reliability
• Developed test harnesses and tools to facilitate the execution of automated tests