Senior Data Scientist
Fourkites
IndiaPosted 8 days ago
Skill Required
Engineering JobsData ScientistMachine LearningAgileand
Key highlights
- Competitive compensation with stock options
- Senior Data Scientist level role
- 36 PTO days plus 5 recharge days
- Strong ML fundamentals across regression, classification, and time‑series forecasting required
- Experience with AWS and Airflow for cloud data pipelines
- NLP/LLM experience for extraction pipelines
Role overview
FourKites enables global supply chain visibility and efficiency, helping customers like Cardinal Health and Walmart with real‑world logistics challenges. As a Senior Data Scientist, you will own end‑to‑end machine learning models that drive core predictions such as ETA/ATA forecasting and text‑based status extraction, collaborating closely with product, engineering, and operations teams.
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, 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
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, not just 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
Benefits
- Competitive compensation with stock options
- Medical benefits start on first day of employment
- 36 PTO days (Sick, Casual and Earned), 5 global 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.)
- Parental leave for all parents
- Annual wellness stipend
- Diversity and inclusion initiatives throughout the year
Additional details
- FourKites processes over 3.2 million supply chain events daily and serves 1,600+ global brands
- FourKites Intelligent Control Tower® creates a real‑time digital twin of orders, shipments, inventory and assets
- FourKites is an equal opportunity employer that celebrates diversity and fosters an inclusive environment
- Originally posted on Himalayas