Data Scientist(AI/ML Engineer)

Job Title: AI/ML Engineer Location: Fort Mill, South Carolina(Hybrid) Employment type: Contract Experience- 10+ Years Must have: 3+ years shipping LLM features in production: prompt/versioning, output validation, fallbacks. Experience with RAG or controlled generation under policy filters (input/output). Job Description: We are seeking a highly skilled Data Scientist with strong AI/ML experience.. The ideal candidate will have a strong background in data science, machine learning, and statistical modeling, with hands-on expertise in building and deploying models at scale. This role will work closely with business stakeholders, data engineers, and product teams to deliver AI-driven insights and solutions that support key business decisions. \_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_ Key Responsibilities: • Design, develop, and implement machine learning and AI models to solve business problems. • Perform data wrangling, preprocessing, and feature engineering using large, complex datasets. • Apply advanced techniques in predictive analytics, natural language processing (NLP), computer vision, and deep learning as per project needs. • Collaborate with data engineers to ensure seamless data pipelines and model deployment in production environments. • Conduct model evaluation, validation, and performance monitoring to ensure accuracy and scalability. • Work with stakeholders to translate business requirements into data-driven solutions. • Stay up to date with emerging AI/ML technologies, frameworks, and best practices. \_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_ Required Skills & Qualifications: • Master’s or Ph.D. in Computer Science, Data Science, Statistics, Mathematics, or related field. • 10+ years of experience in data science or applied machine learning roles. • Strong programming skills in Python, R, or Scala. • Experience with ML frameworks such as TensorFlow, PyTorch, Scikit-learn, or Keras. • Strong understanding of statistical modeling, supervised/unsupervised learning, and deep learning techniques. • Experience with cloud platforms (GCP, AWS, or Azure) and tools like Databricks or Spark. • Familiarity with CI/CD pipelines, MLOps practices, and deployment of ML models in production. • Strong communication skills to explain technical concepts to non-technical stakeholders. \_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_ Preferred Qualifications: • Experience working in large-scale enterprise environments (telecom/retail/financial domain is a plus). • Hands-on exposure to NLP, computer vision, and reinforcement learning. • Experience with data visualization tools such as Tableau, Power BI, or Python visualization libraries. • Knowledge of data governance, compliance, and model explain ability.