Engineer - Data Science

Role Overview

Responsibilities

• Deliver project architecture, technical outputs, and project execution throughout the technology lifecycle.
• Develop end-to-end data science and data engineering pipelines and solutions with multidisciplinary teams.
• Implement technical architectures for projects and products with data engineering and data science teams.
• Design and develop production-quality intelligent power technology products and systems.
• Work with experts in deep learning, machine learning, distributed systems, program management, and product teams.
• Apply Agile methodologies and development tools during project delivery.

Qualifications

• Master’s degree in Data Science.
• At least 2 years of progressive experience delivering technology solutions in a production environment.
• At least 2 years of practical data science experience applying statistics, machine learning, and analytics to business problems.
• At least 2 years of experience working with customers to develop requirements and deliver solutions as an architect.

Technical Skills

• Statistical methods include Bayesian networks and hypothesis testing.
• Hands-on development of deep learning and machine learning models for engineering applications.
• Experience with time-series modeling, anomaly detection, root cause analysis, diagnostics, prognostics, pattern detection, and data mining.
• Programming knowledge in Python, R, MATLAB, C/C++, Java, PySpark, SparkR, and Scala.
• Experience with Azure ML Pipeline, Databricks, MLflow, and MLOps.
• Knowledge of computer vision, natural language processing, recommendation systems, optimization techniques, and IoT technologies.
• Experience with Agile software development tools including Jira, Bitbucket, and Confluence.
• Knowledge of OpenCV, GStreamer, OpenVINO, ONNX, TensorFlow, PyTorch, Caffe, Scikit-learn, Keras, Spark ML, NumPy, and Pandas.

Working Style