Data Scientist

Job Description

Job Description

We are looking for a Data Scientist to join a cutting-edge team in Columbia, SC. This role is suited for a hands-on, detail-oriented individual who can quickly step into an established engineering environment and contribute as an individual contributor alongside a stable, collaborative team. You will work closely with software engineering partners to build data-driven solutions, support analytics initiatives, and apply machine learning and ETL expertise to business needs.

Responsibilities:

• Develop, maintain, and improve data pipelines that collect, transform, and prepare information for analytical and operational use.

• Design and implement machine learning models that address business challenges and support data-informed decision-making.

• Partner with software engineers, product stakeholders, and quality teams to integrate data science solutions into broader technical workflows.

• Analyze complex datasets to identify trends, generate insights, and recommend practical next steps based on findings.

• Step into ongoing initiatives with minimal ramp-up time by reviewing existing work and continuing progress on active projects.

• Translate business questions into structured analytical approaches, selecting appropriate methods, tools, and validation techniques.

• Document methodologies, model performance, and data processes to support knowledge sharing and maintainability across the team.

• Participate in periodic onsite collaboration in Irmo, South Carolina, with in-person attendance expected once per quarter.

• Experience in a Data Scientist or closely related role within a technology-focused environment.
• Strong background in ETL processes, including extracting, transforming, and loading data from multiple sources.
• Hands-on experience building, testing, and refining machine learning models for real-world applications.
• Ability to work effectively as an individual contributor while collaborating with cross-functional technical teams.
• Proficiency in analyzing large or complex datasets and communicating findings in a clear, actionable manner.
• Strong problem-solving skills with the ability to continue existing workstreams and adapt quickly to team priorities.
• Comfortable working in a hybrid collaboration model with onsite presence required once per quarter.