Data Scientist

About GlobalLogic GlobalLogic, a Hitachi Group Company, is a leader in digital engineering. We help brands across the globe design and build innovative products, platforms, and digital experiences for the modern world. By integrating experience design, complex engineering, and data expertise, we help our clients imagine what’s possible and accelerate their transition into tomorrow’s digital businesses. Headquartered in Silicon Valley, GlobalLogic operates design studios and engineering centers around the world, extending our deep expertise to customers in the communications, automotive, healthcare, technology, media and entertainment, manufacturing, and semiconductor industries. About the Role: At GlobalLogic, we are looking for a Machine Learning Engineer with strong analytical capabilities and hands-on experience in model evaluation, data manipulation, and scalable benchmarking frameworks. This role is ideal for someone passionate about understanding how ML models behave in real-world conditions and driving model improvements through rigorous testing. Your work will play a critical role in ensuring model accuracy, reliability, and performance at scale. Job Responsibilities: Design and implement a scalable, reproducible benchmarking pipeline in Python. Develop and run benchmark tests on a time-series forecasting model using GCP Vertex AI infrastructure (e.g., Workbench, Pipelines, Training Jobs). Analyze and evaluate model performance across a wide range of metrics, data segments, and forecasting scenarios. Detect and document anomalous behaviors or inconsistencies in predictions, ensuring reliable outputs from ML systems. Produce clear and actionable reports and visualizations to communicate insights to technical and non-technical stakeholders. Continuously improve benchmarking tools and stay up-to-date with best practices in ML evaluation and time-series modeling. Minimum Qualifications: 3 years of hands-on experience in Python development with a strong foundation in libraries such as Pandas, NumPy, Scikit-learn . Solid understanding of machine learning evaluation metrics , especially for forecasting and time-series models . Experience in data manipulation, cleaning, and feature engineering . Strong analytical and troubleshooting skills with the ability to investigate model anomalies or performance drops . Excellent communication skills and the ability to work independently while managing timelines. Preferred Qualifications: Hands-on experience with Google Cloud Platform (GCP) , especially Vertex AI tools like Pipelines and Workbench. Experience building, training, or analyzing Neural Networks . Proven background in time-series forecasting . Familiarity with MLOps practices and containerization tools such as Docker . Experience working with Git and CI/CD workflows. Why Join Us? At GlobalLogic, you'll be part of a collaborative team that values innovation and continuous learning. You’ll have the opportunity to work on impactful AI/ML projects that are shaping the future of technology while growing your career in a supportive and fast-paced environment.

Location: México, MX

Posted Date: 5/29/2025