Senior Data Scientist

Job not on LinkedIn

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🇮🇳 India – Remote

⏰ Full Time

🟠 Senior

📊 Data Scientist

👻 Ghost score 10%

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FourKites, Inc.

WebsiteLinkedInAll Job Openings

501 - 1000 employees

Founded 2014

📦 Logistics

🍽️ Food & Beverage

🏭 Manufacturing

Logistics • Food & Beverage • Manufacturing

FourKites, Inc. is a leading global supply chain visibility platform, leveraging real-time data and advanced artificial intelligence to revolutionize how organizations manage their supply chains. With a powerful suite of applications providing insights on transportation, inventory, yard management, and more, FourKites offers comprehensive solutions to optimize efficiency, reduce costs, and improve customer service for over 1,500 major brands. Trusted by Fortune 500 companies, FourKites integrates seamlessly with enterprise systems, delivering unparalleled visibility across all modes of transport and industries such as food & beverage, pharmaceuticals, and manufacturing.

📋 Description

• Build and own machine learning models powering ETA/ATA forecasting and message-based status extraction • Design, build, and productionize ML models using regression, classification, and time-series forecasting • Develop NLP/LLM-based extraction pipelines for message-based ETA and status updates • Own models end-to-end from data pipeline and training through deployment, monitoring, and retraining • Work with noisy real-world logistics and supply chain data, including GPS pings, check calls, and 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, such as Grafana, to detect drift and degradation • Replace manual or rule-based processes with ML-driven automation • Translate model performance improvements into operational savings, efficiency gains, and deal-relevant outcomes • Mentor and guide data scientists and engineers on technical approaches and best practices • Make build-vs-buy and architecture tradeoff decisions independently • Collaborate closely with product, engineering, and operations teams

🎯 Requirements

• Strong ML fundamentals across regression, classification, and time-series forecasting • NLP experience — text extraction, entity recognition, or LLM-based extraction • Production ML experience shipping models serving real traffic • Strong Python and SQL skills • Experience with pandas and scikit-learn • Experience querying large datasets; Redshift/Snowflake a plus • Experience with AWS, including S3 and EC2 • Experience with orchestration tools such as Airflow for training/retraining pipelines • Experience with model monitoring and observability tooling such as Grafana • Comfortable working with noisy, real-world data • Experience diagnosing and closing the gap between offline evaluation and live production performance • Track record of replacing manual/rule-based processes with ML solutions • Ability to translate model output into business value and communicate impact to non-technical stakeholders • Experience collaborating with product, engineering, and operations teams • Experience mentoring or guiding data scientists or engineers • Ability to make build-vs-buy and architecture tradeoffs independently • Track record of reducing manual intervention or turnaround time through automation • Excellent oral and written communication skills • Experience in logistics, supply chain, or transportation is nice to have • Familiarity with real-time/streaming data (Kafka) is nice to have • Exposure to LLM/GenAI applications in production is nice to have

🏖️ Benefits

• Competitive compensation with stock options • Outstanding benefits • 5 global recharge days • Generous PTO and standard holidays • Parental leave for all parents • Annual wellness stipend • Volunteer days • 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