Top Data Science Jobs in Charleston, SC

The Data Scientist will build analytics infrastructure, conduct analysis and modeling, and collaborate with teams to enhance data impact and insights. Responsibilities include exploratory analysis, model building, and maintaining datasets for student success and operational efficiency.

The Data Scientist will analyze user behavior, create segmentation strategies, design experiments, and track business metrics to drive growth in a SaaS company.

As a Data Scientist, you will develop algorithms, collaborate on product requirements, and communicate data-driven insights, while enhancing product offerings and delivering actionable insights.

As a Senior Data Scientist, you will collaborate with cross-functional teams to drive AI/ML product development, analyze user data, and influence product strategies.

Lead development of a greenfield data product by partnering with customers and product teams to build analytics and models (simulation, Bayesian networks, optimization, ML). Maintain existing analytics, improve predictive churn models, and translate customer needs into production-grade SQL/dbt pipelines, dashboards, and data-driven product features.

The Data Scientist will lead quantitative research projects, manage datasets, mentor junior analysts, and translate findings into actionable insights for clients.

The Data Scientist at GenLogs will build machine-learning systems, analyze large datasets, and collaborate with engineering and product teams to deliver advanced logistics intelligence solutions.

The Data Scientist will build and operate models to improve logistics operations, focus on driver behavior, and analyze data for better delivery efficiency.

The Applied Data Scientist III will develop scalable AI solutions, analyze data, and translate technical concepts for stakeholders while advocating for AI adoption.

The Data Scientist II will work with sports tracking data to build models and analyses for NHL and NBA organizations, focusing on data transformation and metrics development.

The Lead Risk Analytics Data Scientist will develop risk pricing, design data models, automate workflows, and communicate insights to leadership. Responsibilities include owning the risk narrative, building analytics foundations, and utilizing AI to enhance efficiency.

As the Staff Data Scientist, you will lead the data science function, driving strategy, mentoring peers, and shaping product direction through advanced analytics and experimentation.

The Data Scientist will work with the team to build and optimize models, interpret data, and support product development using massive data sets for advertising effectiveness.

Lead the development of outfit completion models by combining client preferences and machine learning to improve personalized recommendations at Stitch Fix.

As a Senior Data Scientist, you will lead high-complexity projects, develop ML and NLP solutions, and collaborate across teams to drive business impact through statistical modeling and data analysis.

This role involves partnering with sales to design data-driven solutions, engaging with customers, and supporting pre-sales engagements.

The Data Scientist collaborates with stakeholders to develop machine learning applications, analyze data, and enhance team operations, improving processes with data-driven insights.

Lead end-to-end data science projects: build, deploy, and monitor ML models (credit risk, pricing, collections, fraud). Partner cross-functionally, productionize pipelines, write production-grade code, and communicate results to technical and non-technical stakeholders.

As a Staff Data Scientist, you'll develop and deploy machine learning models to enhance renter experiences and optimize property partnerships, collaborating across teams to translate data insights into actionable strategies.

The Data Scientist will apply causal inference and data analysis to optimize marketing strategies, collaborate with teams, and lead internal research efforts.

The Data Scientist supports customer use of the Epistemix platform through data integration, modeling, and visualization, improving decision-making and customer satisfaction.

Design, develop, and deploy production machine learning models to improve decisioning for consumer lending. Partner with business and technical teams to develop data sources, improve modeling methodology, manage models in production, and mentor others while practicing strong software engineering and MLOps practices.

The Data Scientist will develop and oversee measurement systems, analyze customer behavior, enhance marketing strategies and translate data insights into actionable business recommendations.

The Marketing Data Scientist will analyze data, onboard clients, develop data pipelines in R, and propose improvements to enhance efficiency.

The Research Data Scientist analyzes viewing data, develops machine learning models, builds data pipelines, and innovates new methodologies for measurement challenges in advertising.