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Tier-1 brand, mid-level ML role, metro location and popular title create high applicant competition.
Core ML skills are transferable across industries, though consumer-marketing domain knowledge adds moderate specificity.
Explicit 2–4 year requirement plus mandatory ML, cloud, and DevOps skills raises shortlisting strictness to high.
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Design and develop scalable Data Science algorithms incorporating Operations Research, ML models, and Generative/Agentic AI techniques.
Collaborate with Data and AI Engineering teams to productionize algorithms and manage large datasets in cloud environments.
Mentor peers and become recognized as a technical expert, driving measurable business improvements through data science solutions.
Education: Bachelor's, Master's, or postgraduate degree in quantitative fields (Operations Research, Computer Science, Engineering, Applied Mathematics, Statistics, Physics, Analytics, etc.).
Experience: 2-4 years of relevant work experience in data science or related roles.
Technical skills: Proficiency in Python and familiarity with libraries like OpenCV, scikit-learn, PyTorch, TensorFlow/Keras, Pandas; capable of coding in cloud environments.
Work Experience Required: 2-4 years
Experienced in applying advanced analytic methodologies including machine learning, optimization, simulation, and Generative/Agentic AI to business problems.
Familiar with cloud computing platforms (GCP or Azure) and DevOps tools (Git, CI/CD).
Capable of working cross-functionally with domain experts and engineering teams, owning delivery from design to production with technical mentorship responsibilities.