Deepak Ravikumar Sriram
Senior Ai Ml Scientist Enginneer Ii @Nielsen
Signup · Get unlimited contacts
WORK HISTORY
Senior Ai Ml Scientist Enginneer Ii @Nielsen
London, GB
Product: Marketing Measurement – USA Age/Income/Ethnic Audiences, Nielsen ONE Ads (B2B SaaS) Drove £24M in annualized revenue by leading a 5 member cross functional team to develop a media measurement product across Connected TV (e.g: Netflix) and Digital platforms Led 0->1 data science efforts in implementing a sequential data science framework based on Gradient Boosting and Negative Binomial algorithms, improving multi-class prediction estimates by 19% Orchestrated the implementation of measurement solution with data engineering and UI team for ad campaigns leveraging AWS, Apache Spark and Airflow Provided continuous monitoring and support in terms of production bug fixes, product releases, ad-hoc client requests Worked closely with product/leadership in scoping and translating products requirements to data science roadmaps Feature: Ad viewing Deduplication, Nielsen ONE Ads (B2B SaaS) Ideated, developed, scaled and deployed a Bayesian model-based deduplication feature to estimate measurement disjoints across media platforms - integrated feature drove an incremental revenue of £1.8M in 2024 Supported end-to-end adoption of the feature across the organization and served as a company wide point of contact/expert for multiple business functions (such as content measurement) POC Feature: Ad viewing Deduplication – Privacy protected audiences, Nielsen ONE Ads (B2B SaaS) Pioneered a framework to measure privacy protected campaigns across walled garden publishers such as Google using sketches (probabilistic data structures)
EDUCATION
Birla Institute of Technology and Science, Pilani
Bachelor's degree, Engineering
UMN Carlson School of Management
Master's degree, Data Science & AI
ABOUT DEEPAK RAVIKUMAR SRIRAM
I am a data science professional with close to 5 years of advanced analytics experience in CPG, retail and financial services. My work across marketing, customer experience and credit risk analytics includes: 1. Data Mining with SQL, Hadoop, Hive; ETL with Teradata 2. Machine Learning : SVM/Random Forest/Gradient Boosting/Logistic Regression in R and Python3. Natural Language Processing : Text Mining, Sentiment Analysis, LDA, Topic Modeling using Python4. Exploratory Data Analysis and Visualizations using R and Tableau5. Statistical Analysis, Design of Experiments, Forecasting and Hypothesis Testing in R6. Credit Risk Management, IFRS 9 and BASEL 3 modeling, Loss Forecasting in SAS
This profile is compiled from publicly available professional sources. Unifers is not affiliated with or endorsed by LinkedIn. Request removal of this profile.