About the role:

As a Data Scientist at Symphony Industrial AI, you will be ideating and creating solutions for some of the most complex industrial problems utilizing our cutting-edge AI/ML platform.

By developing and blending some of the best-in-class AI/ML methods for multivariate time series data, images, semi- and unstructured data including text, with core asset maintenance and process control systems, you will build new groundbreaking solutions that will fundamentally alter predictive maintenance and operational optimization.

Key Responsibilities:

- Interact and collaborate with engineers, data scientists, domain experts, and product managers to identify and discover insights from customers to continually develop our products.

- Directly interact with customers & domain experts across industries to understand and help solve their business problems.

- Become a master advocate and leader of Symphony Industrial AI's products.

- Serve as a technical and subject matter expert for sales meetings and events.

- Carry out exploratory analysis of industrial data.

- Build and deploy predictive AI, generative AI and agentic AI solutions for industrial use cases.

Tech Stack & Requirements:

- Bachelor's or master's in a quantitative field and engineering.

- 5+ years of utilizing Machine Learning in an industrial or related organization.

- Solid understanding of statistics and machine learning algorithms.

- Expertise with Python-based data science toolkits like Scikit-learn, TensorFlow, Keras, Pandas.

- Experience and expertise in first principles modeling, dynamic optimization, signal & image processing, NLP is highly preferable.

- Ability to translate analytic ideas into code using production-quality Python code.

- Familiarity with agile development methodology, git version control, Linux OS, and use of API services.

- Experience with solutions running off historians (OSI PI, IP21, etc.) and SCADA DCS systems (ABB, GE, Siemens, etc.) and familiarity with connection protocols such as OPC UA/DA, ODBC, etc.

- Experience with deploying solutions on cloud infrastructure (Azure, AWS, Google).

- Extremely good, proven problem-solving skills.

- Ability to travel as needed.