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Vacancy description

Senior Data Scientist in Chennai, भारत

Fourkites

  • Full-timeStandard weekly hours

Chennai, भारत

At FourKites we have the opportunity to tackle complex challenges with real-world impacts. Whether it's medical supplies from Cardinal Health or groceries for Walmart, the FourKites platform helps customers operate global supply chains that are efficient, agile and sustainable. Join a team of curious problem solvers that celebrates differences, leads with empathy and values inclusivity. As a Senior Data Scientist, you will build and own machine learning models that power core prediction problems across the FourKites platform — including ETA/ATA forecasting and message-based status extraction. You will work end-to-end, from data pipeline to production deployment and monitoring, turning noisy real-world logistics data into models that run at scale and directly move the needle on customer outcomes. You will work closely with product, engineering, and operations teams, hands-on building and shipping models yourself while also guiding the technical direction of other data scientists on the team.

What you'll be doing: - 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 → 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 — operational savings, efficiency gains, and deal-relevant outcomes - Mentor and guide other data scientists/engineers on technical approach and best practices - Make build-vs-buy and architecture tradeoff decisions independently About the team: Our product and engineering teams are dedicated to providing the industry's best-in-class end-to-end supply chain visibility platform. We are committed to building a high-performing, ML-driven team that turns supply chain data into automated, proactive action — and we want you to help lead that effort.

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