Decision Scientist II

GrubHub•New York, NY

51d

About The Position

The Fulfillment Data Science team at Grubhub is dedicated to building predictive ML models within the fulfillment services space, such as delivery estimation, dispatch, scheduling, and driver pay. We are seeking a Data Scientist II to join this innovative and collaborative team. This role will involve developing state-of-the-art machine learning models, working closely with engineering and product teams, and driving impactful solutions to complex logistics challenges.

Requirements

Educational Background: Advanced degree in a quantitative field such as Computer Science, Data Science, Mathematics, Engineering, Statistics, or equivalent experience.
ML Expertise: 3+ years of experience with machine learning libraries such as XGBoost, PyTorch, TensorFlow, or similar frameworks. Familiarity with decision trees, gradient boosting, and deep learning techniques.
Programming Skills: Strong proficiency in Python, including data manipulation libraries (Pandas, NumPy) and distributed computing frameworks (PySpark, Hive).
Business Acumen: Proven ability to translate business requirements into ML solutions with measurable impact. Experience in logistics, fulfillment, or operations is a plus.
Data Engineering: Hands-on experience with data preparation, feature engineering, and handling large datasets in a distributed environment.
Communication: Ability to clearly articulate complex technical ideas to diverse audiences, including leadership and non-technical stakeholders.
Problem-Solving: A passion for tackling ambiguous, complex problems and delivering innovative solutions.
Continuous Learning: A growth mindset with a deep interest in staying updated on the latest advancements in machine learning and logistics.

Responsibilities

Develop and Enhance Predictive Models: Design, build, and optimize machine learning models to improve delivery estimation, dispatching efficiency, driver pay optimization, and scheduling reliability.
Collaborate Across Teams: Partner with Product, Engineering, and Operations teams to define model objectives, gather requirements, and align ML solutions with business goals.
Innovate with Cutting-Edge Techniques: Leverage tools like H2O, XGBoost, and AWS (Sagemaker, EMR, S3, EC2) to implement scalable solutions that meet Grubhub's high performance and accuracy standards.
Optimize Key Metrics: Establish and monitor KPIs for ML models, continuously improving business outcomes such as fulfillment efficiency, diner satisfaction, and operational costs.
Contribute to MLOps Excellence: Participate in discussions for improving the MLOps framework for streamlined model development and deployment, ensuring robust performance and reproducibility.
Promote Data-Driven Insights: Communicate findings, model performance, and recommendations effectively to technical and non-technical stakeholders.

Benefits

PTO. Grubhub employees enjoy a generous amount of time to recharge.
Health and Wellness. Excellent medical, dental and vision benefits, 401k, employee network groups and paid parental leave are just a few of our programs to support your overall well-being.
Free Meals. Our employees get a weekly Grubhub credit to enjoy.
Social Impact. At Grubhub we believe in giving back through programs like the Grubhub Community Fund. Employees are also given paid time off each year to support the causes that are important to them.

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