Senior Simulation Scientist

Symbotic Inc.•Wilmington, NC

54d•Hybrid

About The Position

With its A.I.-powered robotic technology platform, Symbotic is changing the way consumer goods move through the supply chain. Intelligent software orchestrates advanced robots in a high-density, end-to-end system - reinventing warehouse automation for increased efficiency, speed and flexibility. As a Senior Simulation Scientist, you will play a key role in the development of data pipelines and infrastructure for simulation, machine learning and re-enforcement learning. We're seeking a versatile Simulation Scientist who thrives at the intersection of software, data engineering and data science. You'll be responsible for building robust data pipelines, architecting scalable infrastructure, and automating advanced analytics and machine learning to solve real-world business problems. If you love both wrangling messy data and building models that drive decisions, this role is for you. You'll be part of a cross-functional team that blends software engineering, system design, and data science to drive strategic decisions and optimize complex systems.

Requirements

A bachelor's or master's degree in Computer Science, Data Science, Statistics, or related discipline provides the academic foundation for success.
Minimum of 6 years of experience in data engineering and/or data science roles.
Experience with data transformation, ETL pipelines, and data wrangling using tools like Python, Pandas, NumPy, or SQL.
Experience with ML and cloud computing models and tools for training in simulation, MLOps and model deployment pipelines.
Direct experience with data science workflows: experimentation, statistical analysis, and visualization.
Knowledge of real-time data processing (Kafka, Flink).
Familiarity with BI tools (Tableau, Power BI, Looker).
Familiarity with machine learning frameworks (scikit-learn, TensorFlow, PyTorch)
Excellent verbal and written communication skills to effectively represent the derived results and to technical and non-technical audiences
Ability to work independently and collaboratively in a fast-paced, iterative environment.

Responsibilities

Design, build, and maintain scalable ETL/ELT pipelines.
Develop and optimize data architectures for simulation, analytics and machine learning.
Ensure data quality, integrity, and security across systems.
Analyze large datasets to uncover trends, patterns, and actionable insights.
Build, validate, and deploy predictive models and machine learning algorithms.
Conduct A/B testing and statistical analysis to support decision-making.
Visualize data and communicate findings to technical and non-technical stakeholders.
Work closely with product managers, analysts, and software engineers to simulate new and existing robots and systems.
Advocate for data-driven decision-making across the organization.