Summary

Overview

Work History

Education

Skills

Websites

Awards

Timeline

Priyanshu Khandelwal

Senior Data Scientist

Noida

Summary

Data Scientist with more than 7 years of experience in solving business problems using statistical & machine learning techniques. Proficient in building robust and scalable ML & AI applications using big data. Experienced in feature engineering, predictive modelling and data processing techniques. Capable of handling teams and creating insightful data-based services to translate business and functional qualifications into deliverables. Well versed in data science tools and holds domain knowledge of Retail, SEO, Payments and Ads, currently in ML innovations and insights in Paytm Advertisements Team. Meticulous Data Scientist accomplished in compiling, transforming and analyzing complex information through software. Expert in machine learning and large dataset management. Demonstrated success in identifying relationships and building solutions to business problems.

Overview

years of professional experience

years of post-secondary education

Work History

Data Science + ML (Digital Advertising, User targeting)

Paytm Ads

08.2022 - Current

Real Time Campaign Selection: ML-driven customer-level scores using RF, LGBM and Logistic Regression for precise advertisement targeting, projecting a 12% monthly revenue boost
Instant campaign selection ensures optimal ad delivery, maximizing performance (CTR and eCPM)
GenAI POC for revenue uplift: Implemented XGBoost model integrating visual creative & advertiser features using GPT-4 text & vision API
POC saw up to 13% performance gain
This led to significant impressions inventory saving, potentially yielding ~5% monthly revenue increase
Audience Targeting: Designed a model to segment and target users akin to high-performing ones in advertiser or category
Aim was to enhance campaign result and advertiser ROI
ML segments showed ~60% higher CTR than rule-based, boosting our platform's CTR by 15%
Customer Persona: Identified customer personas for Paytm Ads and created cohorts of customers based on behavior on Paytm app and ads
This helped us to understand hidden patterns, good/avg customers and active/dormant customers for banner and scratch card targeting.

Data Scientist, Adobe.com (Search Engine Optimization, SEO)

Adobe Inc.

05.2021 - 07.2022

Migration Tracking: Analyzing daily/weekly traffic change in Adobe.com and highlighting it to leadership on regular basis
This helped to track the migration of Adobe’s subdomains and migration’s impact on conversion and revenue
Outreach project: Created an ML based model to understand the impact of outreach on organic traffic
This model is used by managers to estimate future efforts and ROI on their investments in backlink acquisitions
Estimated revenue jump was around $50k per month
Anomaly and Contribution Analysis Model: Managed a team of five including two interns to create an ensembled model using Isolation Forest and SGD to detect anomaly in Adobe's traffic & orders based on weekly KPIs and identify contributing factors
Position Tracking Algorithm: Developed a simple but efficient Adobe internal algorithm using Random Forest and Hierarchical clustering to understand changes in URL position over period of a time, which helped understand our SEO efforts over time
Identifying Similar Keywords and Creating Themes: Used Word2Vec to create cosine similarity-based model to create themes out of 1M keywords
These themes were used to identify new SEO opportunities
Multiple Analytics Projects: Handled multiple insights and analytics projects which were shared with higher leadership to understand the impact of various efforts in SEO to bring more organic traffic
These efforts helped forecast a revenue of $4M for CC & DC Adobe clouds.

Senior Data Scientist, UK Based Client (Ecommerce + Retail)

Dunnhumby India

09.2019 - 05.2021

Point of Market Entry: Designed module to pinpoint customer entry points and preferred products in specific categories, resulting in a 7% revenue increase for the client through enhanced targeting strategies and analysis
Front of Store Missions/Themes: Analyzed Front of Store section using NMF and Clustering on 7M baskets, we created a mission view for vital FOS objectives, revealing shopper engagement patterns and basket composition which resulted in report worth £ 15K per month
POS Customer Segmentation: Built a model to tag customers based on available historic customer segmentation that splits customers based on life stage & affluence
This helped to understand profiles of POS Customers Identifying Cannibalization: Client reported inverse sales behavior after they launched new products
We hypothesized this problem as cannibalization and justified it using Natural Language Processing model based on string matching algorithms & user behavior analysis.

Data Science and Analytics (Retail + Healthcare)

Tata Consultancy Services

01.2017 - 08.2019

Apple Sales Forecasting: Worked on ML modelling for Apple Sales to forecast apple devices sales for upcoming months
MySupply project: Tracked routine changes in Apple devices for every device (outside India Region)
The task was to coordinate with business and send them regular insights about the impact of those changes in business
Change Ownership: Led changes for client software requirements, managed a diverse team and ensured smooth business processes.

Education

Bachelor’s in Computer Science -

01.2012 - 04.2016

Skills

Programming: Python, Visual Basic for Application, SQL, Data Structures and Algorithms

Frameworks & API: PySpark, Scikit-Learn, TensorFlow, NumPy, Pandas, Matplotlib, OpenAI, LLM, MLlib

Machine Learning Algorithms: Regression, Tree based Algorithms, Deep Learning, Clustering, NMF, PCA, SVM, Word2Vec, Bert

Dashboarding/Insights: Microsoft Excel, Looker studio, Power BI

Data Science: Statistical Analysis, A/B Testing, EDA, Statistics, Feature Engineering, Generative AI, Storytelling, NLP, Data Analytics

Miscellaneous & Deployment: AWS, Azkaban, MLOps, Git, Docker, Jupyter, VS code, MLFlow, Flask, Streamlit, FastAPI

Statistical Analysis

SQL Databases