About the Role

Were looking for a Data Scientist with strong applied AI expertise to build, deploy, and scale

data-driven solutions for logistics, and intelligent decision systems. Youll work with large-

scale supply chain data to develop predictive and generative AI models that enhance

operational efficiency and business outcomes.

What this role entail

Design and implement machine learning, deep learning, and AI-driven optimization models for logistics and operations.
Build scalable and robust data preprocessing pipelines and reproducible modelling pipelines.
Conduct A/B testing, model monitoring, and performance tuning to ensure reliability.
Experiment with new models and techniques.
Test performance of data-driven products.

What lands you in this role

1-4 Years of experience in Data Science Model development and deployment
Strong forecasting experience
Must have exposure to developing predictive analytics and machine learning for business applications
Exposure to ML/GenAI frameworks and tools, Apply computer vision or NLP for automation
Use LLMs and GenAI for knowledge extraction, intelligent decision support
Extensive experience with Git, Docker

Technical Skills

Programming: Python, SQL, PySpark

ML/AI Frameworks: Scikit-learn, PyTorch, TensorFlow, XGBoost, LightGBM

Data Engineering: Redshift, Kafka, AWS S3, Snowflake

Model Serving: FastAPI, Triton, Ray Serve, Docker

Visualization: Power BI, Plotly, Tableau

Bonus: LLMs (LangChain, Transformers), Reinforcement Learning, or GNN

Qualifications

B.Tech / M.Tech / M.Sc. in Computer Science, Data Science, Statistics, or related field.
Proven experience deploying ML/AI models in production.
Strong problem-solving and analytical skills with an understanding of SCM.

Nice to Have: Experience with Agentic AI systems, multi-modal AI (vision + text), or real-time

ML.

Data Scientist