Senior Data Scientist - AI Practice Team

Senior Data Scientist - AI Practice Team

Houston, TX, United States and 2 more

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We are seeking an exceptional Senior Data Scientist to join us full-time in our Artificial Intelligence (AI) Practice Team. In this role, you will lead the design and delivery of analytics and machine learning solutions across policy, data, and document-centric AI engagements, working with complex real-world datasets from industrial and asset-intensive domains.

Location:

This position can be based in Houston, Texas;
Knoxville, Tennessee; or Washington, DC.

What You Will Do:

• Lead the preparation, exploration, and analysis of client data (tabular, time-series, and document-based) to enable robust modeling, feature engineering, and insight generation.
• Design, implement, and validate machine learning models and analytics pipelines, including problem framing, model selection, evaluation, and iteration for real-world performance.
• Drive advanced use of NLP and document understanding techniques to extract, transform, and enrich information from reports, PDFs, logs, and other unstructured sources.
• Build and maintain clear, impactful dashboards, reports, and visualizations (e.g., in Python, Power BI, or similar tools) to communicate findings to consultants and client stakeholders.
• Collaborate with consultants and domain experts to translate business problems into analytical solutions, articulate trade-offs, and present recommendations to technical and non-technical audiences.
• Ensure technical quality, reproducibility, and governance by establishing good practices for code, documentation, data management, and model tracking across projects.
• Mentor and support junior data scientists, providing guidance on methods, tooling, and best practices, and reviewing their work for quality and consistency.

What You Will Need:

Education and Experience

• Bachelor’s degree in a STEM discipline (e.g., Data Science, Computer Science, Engineering, Mathematics, Statistics) or related field;
  Master’s degree preferred or equivalent experience.
• 5+ years of experience applying data science and machine learning in professional settings, including end-to-end delivery of analytics/ML solutions.
• Proven track record working with real-world, messy datasets (including unstructured/document data) across the full lifecycle: data preparation, modeling, evaluation, and deployment handoff.
• Experience leading or owning significant work streams within AI/ML or analytics projects, ideally in consulting, industrial, or asset-intensive environments.
• Practical experience working with cloud-based and modern data platforms (e.g., Azure, AWS, GCP, Databricks) and integrating with enterprise data sources and workflows.

Knowledge, Skills, and Abilities

• Deep proficiency in Python for data science (pandas, scikit-learn, and related libraries) and strong SQL skills for working with relational and analytical data stores.
• Strong grounding in statistics, machine learning, and model evaluation, including supervised/unsupervised methods, feature engineering, and performance diagnostics.
• Hands-on experience with NLP and document understanding (e.g., text preprocessing, embeddings, classification, information extraction, transformers/LLMs) applied to real datasets.
• Ability to design and implement robust, maintainable analytics and ML pipelines, using notebooks and production-ready code with Git-based version control.
• Familiarity with modern data and ML tooling (e.g., Databricks, MLflow, Docker, CI/CD for data/ML) and good practices for experiment tracking and reproducibility.
• Proficiency with BI/visualization tools (e.g., Power BI, Tableau) and data storytelling skills to communicate complex analytical results to non-technical stakeholders.
• Excellent communication and stakeholder engagement skills, with the ability to frame analytical approaches, explain trade-offs, and align solutions with business objectives.
• Proven ability to work across multiple projects, manage priorities, and operate in a fast-moving, consulting-style environment, while mentoring junior team members.
• Nice to have: exposure to industrial, maritime, or asset-intensive domains, or prior experience in AI consulting…