Senior Data Scientist

Overview

Senior Data Scientist to build and own machine learning models that power core prediction problems on the FourKites platform, including ETA/ATA forecasting and message-based status extraction, and to guide the technical direction of other data scientists on the team.

What you'll do

• Design, build, and productionize ML models for problems like ETA/ATA prediction, using regression, classification, and time-series forecasting techniques
• Develop NLP/LLM-based extraction pipelines for message-based ETA and status updates (text extraction, entity recognition)
• Own models end-to-end: data pipeline, training, deployment, monitoring, and retraining
• Work with noisy, real-world logistics and supply chain data (GPS pings, check calls, carrier data) rather than clean, pre-processed datasets
• Diagnose gaps between offline evaluation performance and live production accuracy, and drive fixes
• Build and maintain automated training/retraining pipelines using orchestration tools such as Airflow
• Set up and maintain model monitoring and observability (e.g., Grafana) to catch drift and degradation proactively
• Replace manual or rule-based processes with ML-driven automation (e.g., automating manual check calls)
• Translate model performance improvements into business impact, including operational savings, efficiency gains, and deal-relevant outcomes
• Mentor and guide other data scientists and engineers on technical approach and best practices
• Make build-vs-buy and architecture tradeoff decisions independently

What you'll need

• Strong ML fundamentals across regression, classification, and time-series forecasting
• NLP experience: text extraction, entity recognition, or LLM-based extraction
• Production ML experience: you've shipped models serving real traffic, not just POCs or notebooks
• Strong Python and SQL skills, including pandas, scikit-learn, and comfort querying large datasets
• Experience with cloud and data infrastructure, including AWS (S3, EC2) and orchestration tools like Airflow for training/retraining pipelines
• Experience setting up or working with model monitoring and observability tooling (Grafana or similar)
• Comfortable working with noisy, real-world data rather than clean, curated datasets
• Experience diagnosing and closing the gap between offline evaluation results and live production performance
• A track record of replacing manual/rule-based processes with ML solutions
• Ability to translate model output into business value and communicate that impact to non-technical stakeholders
• Experience collaborating cross-functionally with product, engineering, and operations teams
• Experience mentoring or guiding other data scientists or engineers
• Ability to make build-vs-buy and architecture tradeoffs independently
• A track record of reducing manual intervention or turnaround time through automation
• Excellent oral and written communication skills

Nice to have

• Experience in logistics, supply chain, or transportation
• Familiarity with real-time/streaming data (Kafka)
• Exposure to LLM/GenAI applications in production

Details

• Location: Chennai or Remote, India