Senior Data Scientist

<p><em>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.</em></p> <p><em>Join a team of curious problem solvers that celebrates differences, leads with empathy and values inclusivity.</em></p> <p>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.</p> <p><strong>What you'll be doing:</strong></p> <ul> <li>Design, build, and productionize ML models for problems like ETA/ATA prediction, using regression, classification, and time-series forecasting techniques</li> <li>Develop NLP/LLM-based extraction pipelines for message-based ETA and status updates (text extraction, entity recognition)</li> <li>Own models end-to-end: data pipeline → training → deployment → monitoring → retraining</li> <li>Work with noisy, real-world logistics and supply chain data (GPS pings, check calls, carrier data) rather than clean, pre-processed datasets</li> <li>Diagnose gaps between offline evaluation performance and live production accuracy, and drive fixes</li> <li>Build and maintain automated training/retraining pipelines using orchestration tools such as Airflow</li> <li>Set up and maintain model monitoring and observability (e.g., Grafana) to catch drift and degradation proactively</li> <li>Replace manual or rule-based processes with ML-driven automation (e.g., automating manual check calls)</li> <li>Translate model performance improvements into business impact — operational savings, efficiency gains, and deal-relevant outcomes</li> <li>Mentor and guide other data scientists/engineers on technical approach and best practices</li> <li>Make build-vs-buy and architecture tradeoff decisions independently</li> </ul> <p><strong>About the team:</strong></p> <p>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.</p> <p><strong>Who you are:</strong></p> <ul> <li>Strong ML fundamentals across regression, classification, and time-series forecasting</li> <li>NLP experience — text extraction, entity recognition, or LLM-based extraction</li> <li>Production ML experience — you've shipped models serving real traffic, not just built POCs or notebooks</li> <li>Strong Python and SQL skills — pandas, scikit-learn, and comfort querying large datasets (Redshift/Snowflake a plus)</li> <li>Experience with cloud and data infrastructure — AWS (S3, EC2), and orchestration tools like Airflow for training/retraining pipelines</li> <li>Experience setting up or working with model monitoring and observability tooling (Grafana or similar)</li> <li>Comfortable working with noisy, real-world data rather than clean, curated datasets</li> <li>Experience diagnosing and closing the gap between offline evaluation results and live production performance</li> <li>A track record of replacing manual/rule-based processes with ML solutions</li> <li>Ability to translate model output into business value and communicate that impact to non-technical stakeholders</li> <li>Experience collaborating cross-functionally with product, engineering, and operations teams</li> <li>Experience mentoring or guiding other data scientists or engineers</li> <li>Ability to make build-vs-buy and architecture tradeoffs independently</li> <li>A track record of reducing manual intervention or turnaround time through automation</li> <li>Excellent oral and written communication skills</li> </ul> <p><strong>Nice to have:</strong></p> <ul> <li>Experience in logistics, supply chain, or transportation</li> <li>Familiarity with real-time/streaming data (Kafka)</li> <li>Exposure to LLM/GenAI applications in production</li> </ul> <p><strong>Who we are:</strong></p> <p><em>FourKites, the leader in AI-driven supply chain transformation for global enterprises and pioneer of real-time visibility, turns supply chain data into automated action. FourKites Intelligent Control Tower® breaks down enterprise silos by creating a real-time digital twin of orders, shipments, inventory and assets. This comprehensive view, combined with AI-powered digital workers, enables companies to prevent disruptions, automate routine tasks and optimize performance across their supply chain. FourKites processes over 3.2 million supply chain events daily — from purchase orders to final delivery — helping 1,600-plus global brands prevent disruptions, make faster decisions and move from reactive tracking to proactive supply chain orchestration. For more information, visit</em><a href="http://www.fourkites.com"