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Vetted Dashboard Development Professionals
Pre-screened and vetted.
Senior Project Manager specializing in CRM, SaaS, and enterprise IT delivery
Mid-level Chief of Staff specializing in operations and change management
Mid-level Full-Stack Developer specializing in FinTech and Healthcare platforms
Director-level Talent Acquisition leader specializing in scaling teams across tech and adtech
Senior Full-Stack Python Engineer specializing in cloud microservices and MLOps
Junior Data Analyst / ML Engineer specializing in analytics pipelines and recommendation systems
Junior Software Engineer specializing in observability and distributed systems
Entry-level software engineer specializing in embedded systems and industrial IoT
Mid-level Full-Stack Software Engineer specializing in cloud-native data platforms
Senior Marketing Technology Manager specializing in analytics, tracking, and CRM automation
Junior Finance & Strategy Analyst specializing in business analytics and financial modeling
Mid-level Machine Learning Engineer specializing in NLP, recommender systems, and MLOps
Junior Software Development Engineer specializing in ML, NLP, and data visualization
Junior Software Engineer specializing in full-stack development and computer vision
Junior Security Engineer specializing in cloud security and SIEM threat detection
Senior Data Engineer specializing in Cloud Data Platforms and Generative AI
Mid-level AI/ML Product & Solutions Specialist specializing in GenAI and MLOps
Senior Strategy & Operations leader specializing in healthcare and pharmacy growth
Adithya Rajendra
Junior Data Engineer specializing in Azure data platforms and GenAI analytics
“Data/ML practitioner with experience spanning medical imaging (retinal vessel analysis for hypertension/CVD risk prediction) and enterprise data engineering at Carl Zeiss. Built large-scale SAP data cleaning/validation pipelines (10M+ daily records, ~99% accuracy) and RAG-based semantic search with LangChain/vector DBs that cut manual querying by 82%, plus automation that reduced data onboarding from 8 hours to 12 minutes.”