About the company
FourKites is the leader in AI-driven supply chain transformation for global enterprises and pioneer of real-time visibility. The platform processes over 3.2 million supply chain events daily, helping 1,600+ global brands prevent disruptions and move from reactive tracking to proactive supply chain orchestration.
Responsibilities
- 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)
- Diagnose gaps between offline evaluation performance and live production accuracy
- 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
- Replace manual or rule-based processes with ML-driven automation
- Translate model performance improvements into business impact
- Mentor and guide other data scientists/engineers
- Make build-vs-buy and architecture tradeoff decisions independently
Requirements
- Strong ML fundamentals across regression, classification, and time-series forecasting
- NLP experience — text extraction, entity recognition, or LLM-based extraction
- Production ML experience — shipped models serving real traffic
- Strong Python and SQL skills — pandas, scikit-learn, comfort querying large datasets (Redshift/Snowflake a plus)
- Experience with cloud and data infrastructure — AWS (S3, EC2), and orchestration tools like Airflow
- Experience with model monitoring and observability tooling (Grafana or similar)
- Comfortable working with noisy, real-world data
- Experience diagnosing and closing the gap between offline evaluation results and live production performance
- Ability to translate model output into business value
- Experience collaborating cross-functionally with product, engineering, and operations teams
- Experience mentoring or guiding other data scientists or engineers
Nice to have
- Experience in logistics, supply chain, or transportation
- Familiarity with real-time/streaming data (Kafka)
- Exposure to LLM/GenAI applications in production
Conditions
- Competitive compensation with stock options
- 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