Principal Data Scientist

Position Overview:

The Principal Data Scientist will serve as the technical lead driving Porters Data Science efforts. This role expands beyond individual contribution to encompass technical leadership, system architecture, and high-impact innovation. The Principal DS will define how we build, validate, and serve models and ensure our technical roadmap aligns with long-term business goals.

Role Responsibilities

• Strategic Solution Architecture: Partner with Tech and Product Leadership to translate broad business objectives into concrete mathematical and Machine Learning roadmaps. Define what we solve and how we solve it.
• Deep Learning Leadership: Lead the design and deployment of complex Deep Learning architectures (Transformers, LSTMs, Graph Neural Networks) to solve unstructured and non-linear challenges in logistics.
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  Production-Grade Engineering: Bridge the gap between research and production. Ensure all algorithms are written in scalable, production-ready Python and are robust enough to handle high-throughput, real-time decision-making.
• Mentorship & Technical Culture: Elevate the entire data science organisation through mentoring, deep-dive code reviews, and fostering a culture of rigour in statistical methodology and system design.
• Innovation & Applied Research: Investigate and implement state-of-the-art research papers, adapting advanced concepts (e.g., Reinforcement Learning for fleet management) into practical business solutions.

Skills and Qualifications

• Experience & Mindset: 9+ years of rigorous experience deploying scalable solutions, with a preference for deriving algorithms from first principles rather than using out-of-the-box defaults.
• Deep Learning Frameworks: Proficiency in PyTorch or TensorFlow, with ability to apply models such as CNNs, LSTMs, or Transformers to time-series or pattern recognition challenges.
• Mathematical Rigour: Strong command of linear algebra, probability, and convex optimization (MLE, gradient descent) to back up statistical modeling.

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• Python Mastery: Production-grade proficiency in Python and its ecosystem (numpy, pandas, scikit-learn), writing modular, efficient, and deployable code.
• Strategic Communication: Ability to translate complex mathematical concepts for executive strategy while leading deep technical discussions with engineers.

Persona

• 9+ years of experience in Data Science / Machine Learning roles
• 4+ years in senior/lead positions with demonstrated mentorship experience
• Track record of deploying production ML systems at scale
• One of work experience/education to be good pedigree (IIT/IIM/top-tier tech companies)
• Experience in logistics, marketplace, or similar high-transaction-volume domains - good to have but not mandatory
• Published research or contributions to open-source ML projects - good to have but not mandatory