Senior Data Scientist

Kforce has a client in Houston, TX in need of a Senior Data Scientist. Position Summary: We are seeking a Senior Data Scientist to develop and scale advanced AI, machine learning, and analytics solutions that drive risk intelligence, operational decision-making, and business performance. The will be responsible for designing predictive models, developing explainable AI capabilities, leveraging large and complex datasets, and deploying production-grade analytical solutions on modern cloud platforms. The ideal candidate combines strong data science expertise with hands-on experience in Databricks, MLOps, DevOps, and software engineering practices to deliver scalable, reliable, and business-impacting AI solutions. Key Responsibilities:

• Design, develop, validate, and deploy machine learning models for prediction, classification, anomaly detection, scoring, and trend analysis
• Perform feature engineering and data mining using structured and unstructured datasets
• Build explainable AI capabilities that provide transparency into model predictions and key business drivers
• Develop advanced analytics solutions, benchmarking frameworks, forecasting models, and risk assessment methodologies
• Partner with business stakeholders to translate complex business problems into scalable data science solutions
• Build and maintain production-ready data science pipelines and model-serving solutions
• Implement model monitoring, performance tracking, retraining strategies, and governance frameworks
• Contribute to architecture decisions for AI platforms, data products, and enterprise analytics solutions
• Work closely with data engineers, software engineers, and product teams using Agile delivery methodologies

The successful candidate will demonstrate:

• Balance of data science, software engineering, and platform engineering skills.
• Ability to operationalize AI/DS solutions rather than build only experimental models.

Requirements:

• Degree in Data Science, Computer Science, Statistics, Applied Mathematics, Engineering, Operations Research, or related field
• 8+ years of experience developing and deploying machine learning solutions in production environments
• Expert-level proficiency in Python, SQL, and machine learning frameworks
• Strong experience with predictive analytics, statistical modeling, machine learning, and AI solution development
• Experience working with large-scale distributed processing using Spark/PySpark
• Strong knowledge of explainable AI techniques, model validation, and model governance
• Experience implementing CI/CD pipelines for data science and machine learning solutions
• Strong engineering skills using Git, Azure DevOps, GitHub Actions, or similar platforms
• Experience with Infrastructure as Code and automated deployment frameworks
• Deep understanding of MLOps practices including model deployment, monitoring, versioning, observability, and automated retraining
• Ability to build reliable, scalable, and maintainable production-grade AI systems

Hands-on expertise with the Databricks AI Platform, including:

• MLflow
• Unity Catalog
• Feature Engineering/Feature Store
• Model Serving
• Lakehouse Architecture
• Databricks Workflows

Preferred:

• Experience with Generative AI, Large Language Models (LLMs), AI Agents, and Retrieval-Augmented Generation (RAG)
• Experience building enterprise analytics products and customer-facing analytics solutions
• Knowledge of risk analytics, operational intelligence, asset performance management, or compliance analytics
• Experience working in industrial, transportation, energy, maritime, manufacturing, or asset-intensive industries