Mayur Khandelwal

Data Scientist

Bengaluru, Karnataka, India4 yrs 9 mos experience

Most Likely To Switch

Key Highlights

3+ years of experience in Data Science and Analytics.
Proficient in Data Visualization and Business Intelligence.
Hands-on experience with ETL processes and Data Modeling.

Stackforce AI infers this person is a Data Science professional with a focus on Fintech and Environmental Analysis.

Contact

Skills

Core Skills

Data ScienceData Analysis

Other Skills

Amazon AthenaAmazon RedshiftAmazon Web Services (AWS)Amplitude AnalyticsAnalytical SkillsApache AirflowApache KafkaApache SparkArcgis ProductsBashBusiness AnalysisBusiness InsightsC++CSSCleverTap

About

Skilled professional with 3+ Years of Work Experience in the field of Data Science and Analytics in the Fintech Industry. Proficient in various facets of the field including Data Science, Product Analytics, Business Intelligence, Data Visualization, Data Modelling and ETL processes.

Experience

4 yrs 9 mos

Total Experience

1 yr 2 mos

Average Tenure

1 yr 7 mos

Current Experience

Blinkit

Senior Data Analyst

Nov 2024 – Present · 1 yr 7 mos

Juno

Data Analyst

Oct 2023 – Oct 2024 · 1 yr · Bengaluru, Karnataka, India · On-site

All things data.

Jupiter

Data Analyst

Dec 2021 – Sep 2023 · 1 yr 9 mos · Bengaluru, Karnataka, India

Engagement & Growth charter (Rewards, Referral, Giftcards and Homepage)

University of twente

Research Intern

Nov 2020 – Apr 2021 · 5 mos · Remote

Removing the data gaps in the MODIS Terra FSC dataset using a two step filter involving: Spatial and Temporal Filtering. Analysed the accuracy of the processed snow cover dataset with the SNOTEL SWE ground observation stations. Analyzing trends in the snow cover using Mann-Kendall test and correlating it with meteorological (precipitation and temperature) data under different spatiotemporal conditions.

Spatial FilteringTemporal FilteringData AnalysisData Science

The university of tokyo

Research Intern

Jun 2019 – Jul 2019 · 1 mo · Tokyo, Japan

Evaluating the accuracy of TanDEM-X at a global scale. Pre-processed the dataset to create a 3 arcsec resolution 5 x 5 degree tiles using gdal, python and shell scripts. Found and removed discrepancies present in the dataset. Comparison with other widely used DEMs such as ASTER, AW3D and MERIT for some of the major flood plains around the world and error component analysis using ICESat data.

Data Pre-processingError Component AnalysisData ScienceData Analysis