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Tier-1 brand, mid-level generalist ML role, metro location, and broad skill requirements drive high competition.
Core ML, NLP, and data engineering skills are highly transferable across industries.
Explicit 6-year minimum plus many mandatory ML, AWS, NLP, and tooling skills increases shortlisting strictness.
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Lead end-to-end data science projects across multiple business domains including Customer Experience, Operations, Finance, Sales, and Marketing.
Build data pipelines at scale, develop machine learning and predictive models including NLP, and design analytics frameworks for business insights.
Present data-driven insights and visualizations to stakeholders using tools like Tableau/PowerBI and PowerPoint.
Minimum 6 years of experience in data science domain.
Strong proficiency in Python, SQL, and experience with ML frameworks like Scikit-learn, PyTorch, Keras, and NLP libraries (e.g. NLTK).
Experience with Tableau and/or PowerBI, AWS (including SageMaker), and building data pipelines using tools such as Alteryx, GLUE, or Informatica.
Degree preferred in quantitative field (Computer Science, Statistics, etc.); advanced degree (Master’s, PhD) is a plus.
Experienced in delivering predictive analytics solutions for customer retention, pricing optimization, segmentation, and using NLP techniques.
Able to operate independently with minimal supervision in a fast-paced, startup-like environment with consulting experience preferred.
Strong business and communication skills to translate complex data analyses into clear insights for diverse stakeholders.