Data Scientist

Kforce Inc.
Houston, TX, United States
8 days ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
8 years minimum
Working hours
Regular working hours
Job source

Tech stack

Agile Methodology Artificial Intelligence Business Analytics Applications Microsoft Azure Big Data Continuous Delivery Data Architecture Data Mining DevOps Distributed Computing Environment Github Python (Programming Language)
+18 more
Machine Learning Tensorflow Software Engineering SQL Databases Unstructured Data Management of Software Versions Feature Engineering Large Language Models Apache Spark Model Validation Generative AI Git AI Platforms Pyspark Information Technology Deployment Automation Machine Learning Operations Databricks

Job description

Kforce has a client in Houston, TX in need of a Senior Data Scientist., 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., * 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

Benefits & conditions

The pay range is the lowest to highest compensation we reasonably in good faith believe we would pay at posting for this role. We may ultimately pay more or less than this range. Employee pay is based on factors like relevant education, qualifications, certifications, experience, skills, seniority, location, performance, union contract and business needs. This range may be modified in the future.

We offer comprehensive benefits including medical/dental/vision insurance, HSA, FSA, 401(k), and life, disability & ADD insurance to eligible employees. Salaried personnel receive paid time off. Hourly employees are not eligible for paid time off unless required by law. Hourly employees on a Service Contract Act project are eligible for paid sick leave.

Note: Pay is not considered compensation until it is earned, vested and determinable. The amount and availability of any compensation remains in Kforce’s sole discretion unless and until paid and may be modified in its discretion consistent with the law.

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