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Global brand, mid-level generalist Data Scientist (5+ yrs) in hybrid role—high candidate density.
Core ML/MLOps skills transferable, but R&D and consumer-research domain increases domain specificity.
Explicit 5+ years plus mandatory ML, DL, MLOps, and cloud stack skills.
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Lead end-to-end machine learning projects including problem framing, data preparation, modeling, and deployment.
Build and deploy predictive models (regression, classification, clustering, time-series) and design AI agents using LLMs and advanced frameworks.
Collaborate with business stakeholders to translate needs into analytical solutions and deliver projects on time with defined success metrics.
Master’s or Ph.D. in Data Science, Computer Science, Statistics, or related quantitative field.
5+ years of experience building and deploying machine learning models.
Proficiency in Python/R with experience in ML libraries (PyTorch, TensorFlow, Keras) and hands-on MLOps with cloud platforms (AWS/GCP/Azure).
Strong skills in data storytelling and visualization tools (Shiny, Dash, Tableau).
Experienced ML practitioner capable of independently managing multiple projects and full ML lifecycle.
Strong technical expertise spanning classical ML, deep learning, and emerging AI systems like agentic AI and GenAI.
Able to bridge technical solutions and business objectives by effectively communicating with technical and non-technical stakeholders.