Remote Staff Data Scientist Job in United States CompuGain

Who you are

• 7+ years of professional experience or graduate-level coursework in data science, machine learning, statistics, physics, or a related field.
• Advanced proficiency in applying machine learning techniques to real-world problems.
• Advanced proficiency in Python, including expertise in data processing libraries (e.g., spaCy, Pandas), data visualization libraries (e.g., Matplotlib, Plotly), and familiarity with machine learning frameworks.
• Intermediate proficiency with big data technologies and frameworks (e.g., Spark, Hadoop).
• Intermediate proficiency working with the Databricks platform (e.g., Job/Compute, Delta Lake) or a similar platform for data analysis and model training tasks.
• Intermediate proficiency in Bayesian statistics and its application to machine learning.
• Basic proficiency with cloud platforms such as AWS, Google Cloud, or Azure.
• An advanced degree in mathematics, statistics, physics, computer science, or equivalent professional experience.
• Intermediate proficiency in C and C++ is a bonus but not required.

What the job involves

• Research and build groundbreaking machine learning techniques by leveraging Bayesian methodologies, neural networks, regression models, and other state-of-the-art approaches.
• Lead the adaptation and implementation of advanced machine learning techniques to solve customer problems.
• Be at the forefront of applying generative AI techniques to conversational data.
• Conduct independent research into the latest academic papers to develop innovative solutions for customer problems and to support various use cases within our product offerings.
• Refine and advance the mathematical models and algorithms that power our core Bayesian engine.
• Write and optimize code using our data science libraries and frameworks.
• Provide mentorship and guidance to members of our data platform team, including data scientists, data engineers, software engineers, and product managers.
• Document and educate team members on analysis methodologies, models, assumptions, error measurements, data sources, transformations, and tools/processes used in the Invoca Data Science process.
• Support diversity, equity, and inclusion initiatives at Invoca.