The Applied Research team addresses hard, novel challenges that arise in product development or customer engagements. As a Senior Data Scientist, you'll bring your knowledge and proven data science expertise to conduct research in machine learning-based solutions that improve our products and help our customers.
Qualified candidates are deeply analytical with a keen understanding of artificial intelligence, machine learning, and data science. They are experienced researchers who know how to design worthwhile experiments and empirically derive conclusions. They have the ability, inclination, and experience to conduct research that solves practical problems. They have the communication skills to work closely with both research colleagues and customers.
- Independently and effectively engage with internal product developers, external customers, and subject matter experts to understand and solve critical technical challenges through the application of cutting-edge artificial intelligence
- Conduct research and design technical solutions that improve models for commercial and industrial applications, such as anomaly detection, prescriptive maintenance, and fraud detection
- Conduct research on core challenges facing applications of artificial intelligence, such as transparency, explainability, transferability and continuous learning
- Pioneer procedures and/or automated toolsets to more efficiently and effectively perform data science activities
- Contribute to AI product development and key data science research areas, internally and externally
- Propose new projects or initiatives that will yield business benefits and evaluate project plans and proposals
- Evaluate and respond to RFPs related to artificial intelligence
- Conduct research and write patent applications and technical publications
- Serve as a people manager to other data scientists, as needed
- Strong understanding of Data Science, including machine learning, statistics, probability, and modeling.
- Significant experience with Data Science programming languages, such as Python, R, Matlab
- Significant experience with machine learning frameworks, such as PyTorch, TensorFlow, Theano, and Keras.
- Applied knowledge of ML techniques/algorithms including linear models, neural networks, decision trees, Bayesian techniques, clustering, and anomaly detection
- Significant experience managing large volumes of data (terabytes or more)
- Experience with leading project teams, specifically data science teams
- Strong written and verbal communications, ability to translate complex technical topics to internal and external stakeholders