Data Scientist - Remote

Overview

Rev.io is seeking a highly skilled Data Scientist to join our team and drive cutting-edge innovations in machine learning, deep learning, and natural language processing (NLP) applications, focusing on building and optimizing machine learning models that support key business functions.

In Short

• Develop and implement Azure machine learning models for various business applications.
• Design, validate, and optimize AI-driven solutions using machine learning and NLP.
• Collaborate with cross-functional teams to transform business challenges into actionable insights.
• Lead the development and deployment of machine learning models.
• Utilize statistical methods to enhance model performance.
• Communicate technical findings to both technical and non-technical stakeholders.
• Stay updated with advancements in AI technologies.
• Manage end-to-end development of analytic and predictive models.
• Train and iterate on models to ensure optimal performance.
• Conduct experiments to quantify the impact of AI solutions.

Requirements

• Bachelor’s degree in Computer Science, Data Science, or a related field.
• 3+ years of experience with Azure Machine Learning Services/Studio.
• Expertise in data cleansing, feature engineering, and MLOps.
• Experience with libraries such as pandas, NumPy, scikit-learn, and TensorFlow.
• Strong programming skills in Python or R.
• Experience with classification, regression, and NLP best practices.
• Familiarity with AI deployment pipelines and cloud-based solutions.
• Strong understanding of model performance and optimization.
• Excellent problem-solving skills and ability to innovate.
• Strong communication skills to translate technical information.

Benefits

• Generous HSA employer contribution.
• 401k with company match and immediate vesting.
• Unlimited PTO.
• Paid Parental Leave.
• Company paid life and disability insurance.
• Monthly tech and fitness reimbursement.
• Education and development stipend.
• Time off to volunteer.
• Clear career path opportunities.
• Open-door policy for feedback to leadership.