Swaroop Shekar

AI Researcher

Bengaluru, Karnataka, India7 yrs 9 mos experience

Most Likely To SwitchHighly Stable

Key Highlights

Expert in developing predictive models for business insights.
Proven track record in reducing operational efforts through automation.
Strong background in healthcare data analysis and machine learning.

Stackforce AI infers this person is a Data Science expert with a focus on Healthcare and SaaS industries.

Contact

swaroopshekar7@gmail.com LinkedIn

Skills

Core Skills

Machine LearningData ScienceData Analysis

Other Skills

Adobe PhotoshopCollaborative Problem SolvingCommunicationDeep LearningGradient BoostingLeadershipLogistic RegressionMicrosoft ExcelMicrosoft OfficeOpenCVPredictive ModellingPythonRandom Forest

About

Data science professional with experience in implementing data driven solutions to solve business problems. Ability to analyse large amounts of data to derive insights that help businesses in developing strategic plans. Proficient in predictive modelling, data analysis among others

Experience

Goto group

2 roles

Senior Data Scientist

Apr 2024 – Present · 1 yr 11 mos

Data Scientist

Jul 2022 – Apr 2024 · 1 yr 9 mos

Developed and deployed a CNN model to detect 'Low quality' images uploaded by restaurant partners. Which reduced the manual effort of content ops by 18%
Formulated 'Content Quality Score' and built a framework to score merchants based on their content completeness and quality. This comprehensive score can be used for ranking and personalisation of restaurants.
Developed and deployed a ML model pipeline to predict the probability of virgin users making their first order. Model predictions to be used for better targetting of offers.

Machine LearningPythonPredictive ModellingData Science

Unitedhealth group

Data Scientist

Jul 2018 – Jul 2022 · 4 yrs · Bengaluru, Karnataka, India

Built a ‘Heading detection module’ based on OpenCV and Logistic regression model that helps in indexing scanned medical documents
Built a ‘Record-Linkage Tool’ using Python to solve the problem of duplicate member records in Consumer Database
Leveraged historical medical claims data to develop a Gradient boosting model to estimate claim turn around time to reduce call volume at customer service
Designed and developed ‘Application Inventory Mapping utility’ to reduce manual effort in mapping clients’ application portfolio to Standard library
Developed a production model to predict members who are at risk of not adhering to their medications in the next 6 months
Developed a Random forest classifier to identify aberrant claims based on which the pharmacies are shortlisted for the audit process

PythonOpenCVLogistic RegressionGradient BoostingRandom ForestData Science+1