About

Pradeep Adhokshaja is a highly skilled marketing analytics professional with over 5 years of experience in media mix modeling and attribution projects. He is proficient in data analysis tools such as R, Python, SQL, and Data Studio, and is always eager to learn new skills, such as Tensorflow. Pradeep is also a strong communicator and regularly practices his presentation skills through blogging. Currently working as a Data Scientist at Philips, Pradeep is responsible for optimizing the marketing mix for Personal Healthcare Products and helping to optimize portfolio management in the EU markets. He also conducts topic modeling of global feedback to assess pain points and opportunities using sentence transformers, TF-IDF, and K-Means clustering. In his previous role as a Data Scientist at Equifax, Pradeep developed an article recommendation engine for NZ's largest publisher to increase engagement. He also worked on media optimization for Australia's largest FMCG using complex media mix modeling techniques. Pradeep's expertise in statistical and tactical insights was derived through R via the XGBoost algorithm to account for non-linear covariate interactions. Pradeep holds a Bachelor's degree in Electrical, Electronics, and Communications Engineering from the National Institute of Technology Karnataka. He possesses a wide range of technical skills, including data science, research science, deep learning, machine learning, SQL, Python, NLP, Scikit, recommendation systems, XGBoost, Tensorflow, Pandas, and GCP. With relevant experience of 6.78 years, Pradeep is open to new opportunities and collaborations, particularly remote roles that can help him grow as a professional. He can be reached at padhokshaja@gmail.com for any potential opportunities or discussions.