Nov 2024 – May 2025 · 6 mos · Bengaluru, Karnataka, India · On-site

• Led a team of 5+ analysts, to design a category control tower, identifying and validating 100+ BAU metrics for base
• dashboard, improving business and analytics efficiency by 500+ man-hours
• Conducted a root cause analysis (RCA) for negatively rated selection, hypothesized poorly designed catalogs as the
• reason, implemented early detection and removal of poor performing selection, improved selection ratings by 30%
• Spearheaded discounts feature for new user acquisition in Kurta and Kurti sets (KKS) category, implemented static A/B
• testing of the feature, leading to 30% increase in new user acquisition and 10% improvement in KKS sales
• Steered improvement in expectation reality mismatch, proposed introduction of recency factor in visible lifetime average
• ratings, reducing information asymmetry for customers
• Drove RCA for premium pricing in sarees category (60% more than the platform), conducted an in-depth analysis of
• competition pricing, identifying Flipkart’s special pricing burn strategy on matching products

Feb 2024 – Oct 2024 · 8 mos · Bengaluru, Karnataka, India · On-site

Jul 2022 – Dec 2022 · 5 mos · Hyderabad, Telangana, India · On-site

• ● Created several automated tools which helped different teams and systems to work efficiently
• ● Created an HTML page from pandas dataframe and the page was designed using CSS, to summarize the
• different OS linux patch sets which are available across different environments and OS flavours at Apple
• ● Used DateTime module to sort and summarize the data according to the latest release of each month
• ● Used Regular Expression matching module for automated extraction of Apple's internal usage packages
• The efficiency of the query management improved significantly, reducing the existing hundred thousand queries by 75%

Nov 2021 – Jan 2022 · 2 mos · Mexico City, Mexico

• ● Worked with huge dataset of coloured images for classifying into different classes of acne skin problems
• ● Cleaned and augmented the data with various techniques to make the data suitable for a robust model
• ● Building a pyramid network model using ResNet backbone architecture with a pyramidal model on top

Jun 2021 – Jul 2021 · 1 mo · California, United States

• ●Developed 20 high-quality machine learning problems on the MLPro.io IDE, ranging across various difficulty levels
• ● The problems ranged from various topics of the Machine learning and Statistics field involving,
• supervised/unsupervised learning, Neural Networks, Computer vision, NLP, Reinforcement Learning and many more
• ● The work was praised by the manager and problems were rated to be the best and highly interesting among the already existing problems, received an honorarium award of $100 for the work done during the internship

May 2021 – Jul 2021 · 2 mos · Chennai, Tamil Nadu, India

• ●The module allows to create a numerical representation of a voice from a few seconds of audio and to
• use it to condition a text-to-speech model trained to generalize to new voices
• ● A three-stage deep learning-based architecture consisting of encoder, synthesizer, and vocoder was
• developed using python and its dependent deep learning libraries
• ● The model was further optimized using quantization and pruning techniques which not only reduced
• time and size of the model but all provided comparable results to the original model
• ●The project was fast-tracked to implementation and received a stellar recommendation from the company

Jan 2021 – May 2021 · 4 mos

Sep 2020 – Sep 2020 · 0 mo

• ∗ Successfully expanded the brand’s customer base and helped it connect to the student community of MNIT, Jaipur
• ∗ Work was praised by the manager and was awarded with the title of ”Star Intern” by the company

Dec 2019 – Feb 2020 · 2 mos · Jaipur, Rajasthan, India

Sep 2019 – Nov 2019 · 2 mos · Jaipur, Rajasthan, India

Aug 2019 – Nov 2021 · 2 yrs 3 mos · Jaipur, Rajasthan, India

• ∗ Successfully organized several events in cultural and tech fest of the college