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Mid-level ML role at a well-known brand with broad required skills increases applicant competition.
Core ML/MLOps skills transfer across industries, but R&D/consumer-research context moderately favors domain experience.
Requires Master's/PhD, explicit 5+ years, and specific ML, MLOps, and cloud technology skills.
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Lead end-to-end machine learning projects including problem framing, data preparation, modeling, and deployment to production.
Design, build, and deploy scalable ML and AI solutions including predictive models (regression, classification, clustering, time-series) and AI agents using LLMs and related frameworks.
Translate business needs into analytical insights and communicate effectively to both technical and non-technical stakeholders, delivering projects on time with defined success criteria.
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 and ML frameworks such as PyTorch, TensorFlow, or Keras; hands-on experience with MLOps, Git, and cloud platforms (AWS, GCP, or Azure).
Mandatory skills include strong ML expertise, production ML system deployment experience, and data visualization skills (e.g., Shiny, Dash, Tableau).
Experienced in independently leading complex ML projects from end to end in an R&D or product-focused environment.
Comfortable working with both structured and unstructured data applying advanced analytics and deep learning techniques.
Capable of operating at the intersection of technical excellence and business partnership, effectively translating complex analytics into actionable business insights.