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.
Who you are:
- 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 built POCs or notebooks
- Strong Python and SQL skills — pandas, scikit-learn, and comfort querying large datasets (Redshift/Snowflake a plus)
- Experience with cloud and data infrastructure — 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
Who we are:
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 www.fourkites.com.
FourKites provides competitive compensation with stock options, outstanding benefits and a collaborative culture for all employees around the globe. To help you be your best, we have 5 global recharge days, in addition to generous PTO and standard holidays. Parental leave for all parents, an annual wellness stipend and volunteer days also provide you with time and resources for self care and to care for others. Throughout the year, FourKites sets aside time during the workday to learn and celebrate diversity. We're always listening for new ways to support everyone in and out of the office.
Benefits:
- Medical benefits start on first day of employment
- 36 PTO days (Sick, Casual and Earned), 5 recharge days, 2 volunteer days
- Home Office set ups and Technology reimbursement
- Lifestyle & Family benefits
- Mental Wellness support and guidance
- Ongoing learning & development opportunities (Professional development program, Toast Master club, etc.)
FourKites is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.
Hong Kong SAR China