Mahesh Gondi

At Upday’s short-staffed Data Team, I worked as an end-to-end data engineer, from developing data pipelines to creating machine learning solutions and performing analysis. Impact on monetisation & user-experience were the determining factors for prioritization.

Monetisation Analytics - Identifying ad revenue loss, setting up continuous data delivery streams for user consent strings(IAB-TCF) and other ad-revenue sources.

Data Engineering - operating data machinery with Airflow, Kubernetes, Lambda, and Snowplow in AWS and Snowflake.

News Classification - Deployment and manage existing classifier for news articles. Develop PoC using Bert-Transformers for classification task.

Infrastructure Cost Optimisation - Reduced BigQuery cost by €10k/month through query optimisation and systematically improving the underlying data lake storage.

Data Pipelines - Develop, deploy, and maintain various data lifecycle processes with tools like Kubernetes Cluster, Kafka, Cloud Storage, CI/CD, DBT and BigQuery. Setup plans for the mid-long term self-service data-platform.

Omio is a multimodal online travel search & booking platform, based primarily in Europe.

Smart Sorting - Learning-to-rank model aimed at providing users with a unified result view for different travel modes.

Fraud Prevention - Designed and developed in-house ML pipeline to detect payment fraud.

Marketing Performance Optimisation - Analyze SEM performance from business impact and competitor standpoint, improve efficiency of key campaigns by predicting optimal bid price-point.

Development Infrastructure - Provide tools allowing team members to spin up their own jupyter environment on GCP and scale certain pandas-library operations.

Price Accuracy - Enforce price accuracy of the ticket under certain caching/look-to-book constraints.