Data Scientist II

• Develop predictive models using statistical methods, machine-learning algorithms, quantitative reasoning, and creative problem-solving.
• Create reliable predictive features through data exploration, domain knowledge, and advanced feature engineering.
• Perform model diagnostics, validation, and data-quality assessments to evaluate model behavior, stability, and production readiness.
• Improve models by evaluating alternative algorithms, model structures, predictors, and data sources.
• Use R and/or Python to manipulate data, implement algorithms, automate analytical workflows, and support model deployment and monitoring.
• Build monitoring and alerting solutions for data quality, model drift, stability, and predictive performance.
• Support applied generative AI initiatives, including chatbots and conversational AI components for AI phone agents.
• Communicate methodologies, findings, model limitations, and recommendations to technical and nontechnical stakeholders, including senior and executive management.

• Master’s degree in applied mathematics, statistics, computer science, engineering, or another quantitative field.
• Strong foundation in mathematics, statistics, quantitative problem-solving, and machine learning.
• Strong programming and algorithmic problem-solving skills in R and/or Python.
• Ability to write efficient, maintainable analytical code.
• Two to four years of professional experience in data science, machine learning, data engineering, or a closely related field.
• Ability to explain technical work clearly to nontechnical partners.
• Experience working with structured data and building predictive models from complex, real-world datasets.

Apply if you are ready to build production machine-learning solutions and contribute to applied AI initiatives in a collaborative data science environment. This role offers the opportunity to work on consequential business problems while expanding your expertise in statistical modeling, machine learning, and AI.