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Machine Learning Scientist Jobs in Charleston, SC

Varsity Tutors

Business Analytics Tutor

Charleston, SC · Remote

$18 - $40/hr

Ability to explain statistical modeling techniques, machine learning basics, and business ... science to create personalized learning experiences. Through 1-on-1 Online Tutoring, students ...

micro1 AI

AI Trainer - Microbiology Expert

Charleston, SC · Remote

$70 - $90/hr

Prior experience developing or applying rubrics in scientific or educational contexts. * Experience with AI, machine learning, or annotation projects related to biology or microbiology. * Advanced ...

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Showing results 41-60

All JobsMachine Learning Scientist JobsMachine Learning Scientist Jobs in Charleston, SC

Machine Learning Scientist information

See Charleston, SC salary details

$73.8K

$133.9K

$187.6K

How much do machine learning scientist jobs pay per year?

As of Aug 17, 2026, the average yearly pay for machine learning scientist in Charleston, SC is $133,919.00, according to ZipRecruiter salary data. Most workers in this role earn between $116,130.00 and $149,041.00 per year, depending on experience, location, and employer.

What is a machine learning scientist?

A Machine Learning Scientist researches, develops, and applies machine learning models to solve complex problems. They work on designing algorithms, improving model performance, and analyzing large datasets to extract valuable insights. Their role often involves experimenting with new techniques, optimizing existing models, and collaborating with engineers and data scientists to deploy solutions. Machine Learning Scientists typically have expertise in statistics, mathematics, and programming languages like Python. They work in industries such as healthcare, finance, and technology to drive innovation using artificial intelligence.

What does a machine learning scientist do?

A typical day for a Machine Learning Scientist involves collecting and analyzing large datasets, designing and training machine learning models, and evaluating model performance to ensure accuracy and reliability. You'll often collaborate with data engineers, software developers, and domain experts to define project goals, prepare data, and integrate solutions into production systems. Regular team meetings, code reviews, and brainstorming sessions are common, fostering an environment of shared learning and problem-solving. This collaborative structure not only enhances project outcomes but also offers valuable opportunities for continuous professional growth and skill development.

What skills and qualifications are needed to be a machine learning scientist?

To thrive as a Machine Learning Scientist, you need strong skills in mathematics, statistics, programming (typically in Python or R), and a graduate degree in computer science, data science, or a related field. Expertise in machine learning frameworks (such as TensorFlow, PyTorch, or scikit-learn), proficiency with data processing tools, and experience with cloud platforms (like AWS or GCP) are commonly required; certifications in these can be advantageous. Critical thinking, problem-solving, and effective communication are important soft skills for collaborating with cross-functional teams and conveying complex concepts. These abilities enable Machine Learning Scientists to build effective models, deliver actionable insights, and drive innovation within organizations.

Is machine learning a high paying job?

Machine Learning Scientists typically earn high salaries due to the specialized skills required, such as programming, statistical analysis, and experience with tools like Python and TensorFlow. Salaries vary by industry, experience, and location but are generally above average compared to many other tech roles.

What are popular job titles related to Machine Learning Scientist jobs in Charleston, SC?

For Machine Learning Scientist jobs in Charleston, SC, the most frequently searched job titles are:

Machine Learning Scientist jobs near you
Infographic showing various Machine Learning Scientist job openings in Charleston, SC as of August 2026, with employment types broken down into 75% Full Time, and 25% Part Time. Highlights an 75% In-person, and 25% Remote job distribution, with an average salary of $133,919 per year, or $64.4 per hour.

Data Engineering Lead

VIRTUAL CLARITY LIMITED

Charleston, SC • On-site

Full-time

Re-posted 14 hours ago

Job description

Job Description:

DXC Technology is a leading global technology services provider helping the world's largest enterprises and public sector organizations modernize mission-critical systems, optimize operations, and accelerate innovation through AI, cloud, security, and enterprise technology solutions.

Our Insurance Software and Business Process Solutions (ISB) organization partners with insurers worldwide to transform and manage core insurance operations. By combining deep insurance expertise, market-leading software platforms, and AI-powered solutions, we help clients modernize policy administration, claims, billing, underwriting, and digital engagement across Life & Annuity, Property & Casualty, and Specialty Insurance.

Position Summary

The Data Engineering Lead is responsible for the design, development, governance, and operational excellence of enterprise data platforms, pipelines, and analytics capabilities. This role provides technical leadership for data engineering initiatives while managing a team of engineers responsible for delivering scalable, secure, and reliable data solutions that support business intelligence, AI, machine learning, operational reporting, and digital transformation programs.

The successful candidate combines deep technical expertise with leadership skills to establish enterprise data standards, drive modernization initiatives, implement cloud-native data architectures, and ensure data is treated as a strategic business asset. This individual will partner closely with product management, application engineering, cloud operations, architecture, security, and business leaders to deliver measurable business outcomes.

Key ResponsibilitiesData Strategy & Architecture
  • Define and drive the enterprise data engineering strategy and roadmap.
  • Design scalable data architectures supporting operational, analytical, and AI workloads.
  • Establish standards for data modeling, data integration, metadata management, and data lifecycle management.
  • Lead modernization efforts from legacy data environments to cloud-native data platforms.
  • Ensure alignment with enterprise architecture, cybersecurity, and compliance requirements.
Data Platform Engineering
  • Lead the design and implementation of enterprise data platforms utilizing cloud technologies and modern data architectures.
  • Develop and maintain high-volume batch, streaming, and event-driven data pipelines.
  • Build and manage data lakes, data warehouses, lakehouse architectures, and data products.
  • Establish reusable frameworks and accelerators that improve engineering velocity and solution consistency.
  • Drive platform automation through Infrastructure-as-Code and DataOps practices.
Leadership & Team Development
  • Lead and mentor a team of Data Engineers, Data Architects, and Data Integration specialists.
  • Establish engineering best practices and technical standards.
  • Provide technical oversight, architecture reviews, and design guidance across projects.
  • Foster a culture of innovation, accountability, continuous learning, and operational excellence.
  • Support recruitment, onboarding, career development, and performance management activities.
Data Governance & Quality
  • Implement enterprise data governance practices.
  • Establish data quality frameworks, monitoring, observability, and remediation processes.
  • Partner with data stewards and business stakeholders to improve trust in enterprise data assets.
  • Ensure compliance with regulatory, privacy, retention, and security requirements.
  • Define and monitor KPIs related to data quality, availability, and reliability.
AI & Advanced Analytics Enablement
  • Build and optimize data environments that support AI, machine learning, and advanced analytics initiatives.
  • Collaborate with data scientists and AI teams to operationalize models and data products.
  • Support enterprise AI initiatives through governed, trusted, high-quality data pipelines.
  • Establish patterns for feature engineering, model data preparation, and data consumption.
Delivery & Execution
  • Manage delivery of multiple concurrent data engineering initiatives.
  • Create project plans, estimates, resource forecasts, and delivery commitments.
  • Drive agile delivery practices while maintaining governance and quality expectations.
  • Identify risks, dependencies, technical debt, and remediation plans.
  • Ensure predictable delivery, operational stability, and stakeholder satisfaction.
Stakeholder Engagement
  • Work closely with executive leadership to align data investments with business objectives.
  • Partner with engineering, product management, operations, and business teams to prioritize initiatives.
  • Present technical recommendations, investment strategies, and progress updates to leadership audiences.
  • Act as a trusted advisor for enterprise data strategy and modernization initiatives.
Required QualificationsEducation
  • Bachelor's degree in Computer Science, Information Systems, Engineering, Data Science, or related field.
  • Master's degree preferred.
Experience
  • 10+ years of experience in Data Engineering, Data Architecture, or related technology disciplines.
  • 3+ years leading technical teams or enterprise-scale data initiatives.
  • Demonstrated experience designing and delivering enterprise data platforms.
  • Experience leading cross-functional teams in global delivery environments.
Technical Expertise

Strong experience in multiple areas including:

  • SQL and advanced database technologies
  • Python, Spark, Scala, or similar data engineering technologies
  • ETL and ELT frameworks
  • Data Lakes, Lakehouse, and Data Warehouse architectures
  • Cloud platforms (Azure, AWS, or Google Cloud)
  • Databricks, Snowflake, Synapse, Redshift, BigQuery, or equivalent technologies
  • Real-time data processing and streaming architectures
  • API-based integration and event-driven architectures
  • CI/CD, DataOps, Infrastructure-as-Code, and automation practices
Preferred Qualifications
  • Insurance industry experience.
  • Experience supporting AI, Machine Learning, and Generative AI initiatives.
  • Experience implementing enterprise data governance programs.
  • Success leading large-scale cloud migration or data modernization programs.
  • Experience with observability, operational monitoring, and reliability engineering.
Leadership Competencies
  • Strategic Thinking
  • Technical Leadership
  • Decision Making
  • Stakeholder Management
  • Talent Development
  • Executive Communication
  • Continuous Improvement Mindset
  • Customer Focus
  • Results Orientation
  • Cross-Functional Collaboration

At DXC Technology, we believe strong connections and community are key to our success. Our work model prioritizes in-person collaboration while offering flexibility to support wellbeing, productivity, individual work styles, and life circumstances. We're committed to fostering an inclusive environment where everyone can thrive.

If you are an applicant from the United States, Guam, or Puerto Rico

DXC Technology Company (DXC) is anEqual Opportunity employer. All qualified candidates will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, pregnancy, veteran status, genetic information, citizenship status, or any other basis prohibited by law. View postings below .

We participate in E-Verify. In addition to the posters already identified, DXC provides access to prospective employees for theFederal Minimum Wage Poster, Federal Polygraph Protection Act Poster as well as any state or locality specific applicant posters. To access the postings in the link below, select your state to view all applicable federal, state and locality postings. Postings are available in English, and in Spanish, where required. View postings below.

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