Data Scientist II

JOB TITLE

Data Scientist II

LOCATION

Greenville, South Carolina | Onsite

ROLE SUMMARY

Develop, improve, and operationalize machine-learning and AI solutions through predictive modeling, feature engineering, validation, and production deployment. Help maintain and improve an ecosystem of approximately 150 production models while building scalable pipelines, monitoring tools, and model performance solutions.

KEY RESPONSIBILITIES

• 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.

KEY REQUIREMENTS

• 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.