Applied Scientist – Machine Learning & Data Science (US) at Gauss Labs

You are an ideal candidate if you are enthusiastic about delivering products and solutions that are robust and dominant in the market. You thrive in ambiguous environments that require finding the best solution to open problems that have not been solved before. You leverage your exceptional technical expertise in fast-paced research and development and apply your fundamental understanding of computer science, mathematics, and statistics to create reliable, scalable high-performance products. Your strong communication skills enable you to work effectively with both business and technical partners. You have hands-on experience making the right decisions about technical methods. You strive for simplicity and elegance and demonstrate significant creativity and sound judgment backed by real data. Most of all, you are willing to take calculated risks, learn by trial and error, and grow as a team.

Responsibilities

• Design, experiment, develop, and implement AI/ML algorithms
• Understand business problems with insight and experience and do research to find the best solutions to the problems.
• Develop feature engineering/extraction/selection and prediction/classification/anomaly detection algorithms especially for time-series data to solve real-world manufacturing problems
• Use tailored supervised and unsupervised learning methods to tackle various problems occurring in manufacturing and industry in general.
• Deliver high-quality ML solutions based on best practices for exploratory data analysis, proof-of-concept, and development of ML models.
• Collaborate with engineering teams to design and implement software solutions for productization

Key Qualifications

• BS/MS/PhD degree in ML/AI, Data Science, Computer Science, Electrical Engineering (EE), Statistics, Industrial Engineering, Operational Research, Mathematics, or a related field
• Proficiency in algorithm and model development, and model validation for ML/AI applications
• Practical and/or research experience in applying machine learning to solve real-world problems
• Deep expertise in one or more ML/AI disciplines and scientifically versatile demonstrating scientific and industrial maturity.
• Hands-on experience programming in Python, Matlab, R, Java, C++, or other programming languages