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Claro Data Science helps you fast track the infusion of AI into your Applications
Data Deeds Done Dirt Cheap: We optimize our approach to achieve economical AI and data science solutions and services on Web, Mobile and Desktop
We Listen. Learn. Propose. Define KPI.
Implement *Apps/API/SDKs*
Deploy. Measure. Iterate
To get your Data Talking to you
Understand
Meet KPI
Improve
AI-infused App components SDKs
Trained Models and API
Complete Pipelines & Dashboards
Reports and Analysis
That's what makes our company unique.
Krishna is a data scientist and software engineer with over 20 years of experience in digital and TV advertising. Currently he works as a Data Science Engineer at WorkBoard Inc. and as a Principal Data Scientist at Claro Data Science specializing in predictive modeling, NLP, and data engineering. Previously, he held roles at Bridge, Metis, and AudienceScience developed machine learning solutions, taught data science, and optimized ad campaigns. Earlier in his career, he was Chief Scientist at Simulmedia, applying statistical modeling to TV ad optimization, and a Principal Software Engineer at TACODA/AOL, building audience management systems. His work at Real Media Inc. (1996–2003) helped pioneer digital ad tech with the Open AdStream platform. Krishna combines deep technical expertise with a passion for education, having created training programs and talks on topics like deep learning.
Yulia is a data scientist with over five years of experience in ad tech and startups, specializing in machine learning, optimization, and causal inference. At Simulmedia, she developed time series forecasting models, designed impression optimization systems using Java, and pioneered methods to measure TV advertising’s impact on sales. She holds a Master’s n Statistics from Columbia University and a Bachelor’s in Computer Science, Engineering, and Psychology from UPenn , with prior research experience in neuroscience, including co-authoring publication from her work at Mount Sinai. Proficient in Python, R, Java, and big data tools (Hive, Hadoop, Redshift), she enjoys building data pipelines and applying ML to solve business challenges.
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Raman is a mobile architect specializing in GenAI and ML-powered applications, with over 20 years of experience across finance, travel, public sector, and safety tech. He holds a B.Tech from IIT Kanpur and an MS in Computer Science from Rensselaer Polytechnic Institute, where he focused on algorithms for geometric modeling, and 3D mesh generation. He has expertise in Mobile Apps and the integration of AI in Consumer Applications. At MTX he worked on public sector Applications, at Sfara, he worked an AI-based safety SDK adopted by Mercedes-Benz, At Fareportal he increased Mobile conversions in an ecommerce by 30% through predictive analytics and A/B testing. At present Raman is working on a GenAI integrated mobile, native and web/desktop product.
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