Position Overview:
The Principal Data Scientist will serve as the technical lead driving Porter's 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.
- 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.
- 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
