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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior Data Scientist - **Company:** Brooksource - **Location:** Houston, TX, United States - **Experience:** Expert - **Salary:** $145,600.0 - $166,400.0 - **Contract:** Temporary to permanent - **Skills:** Artificial Intelligence, Business Analytics Applications, Microsoft Azure, Cloud Computing, Data Architecture, Information Engineering, Data Governance, Extract Transform Load (ETL), Distributed Computing Environment, Github, Apache Hive, Python (Programming Language), Machine Learning, Release Management, Standard Sql, Azure Machine Learning, SQL Databases, Azure Data Factory, Large Language Models, Generative AI, Git, Data Lakes, AI Platforms, Pyspark, Deployment Automation, Machine Learning Operations, Data Pipelines, Docker, Databricks - **Published:** July 9, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=9758854405b00564 ## About the Role * 7+ years of experience in Data Science, Machine Learning Engineering, Data Engineering, or a related technical field. * Demonstrated experience leading production AI or advanced analytics initiatives within enterprise environments. * Strong hands-on experience with Databricks and Azure Cloud (other major cloud platforms considered). * Advanced proficiency in Python, PySpark, Spark SQL, and SQL. * Experience building scalable ETL/ELT pipelines and modern data architectures. * Experience deploying machine learning models into production using MLOps frameworks and best practices. * Hands-on experience implementing CI/CD pipelines using Git, GitHub, Azure DevOps, or comparable technologies. * Experience working with large-scale distributed data processing platforms. * Strong understanding of data governance, model governance, security, and enterprise AI best practices. * Ability to lead technical initiatives while remaining hands-on with development. * Excellent communication skills with experience partnering across technical teams and business stakeholders., * Experience with Generative AI, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI Agents, or AgentOps. * Experience with MLflow, Azure Machine Learning, Databricks Model Registry, or similar MLOps platforms. * Familiarity with containerization and orchestration technologies such as Docker and Kubernetes. * Experience establishing enterprise AI governance frameworks. * Prior experience within Energy, Oil & Gas, Manufacturing, or other industrial environments. * Experience mentoring engineers or serving as a technical lead. Technical Environment * Azure Cloud * Azure Databricks * PySpark * Spark SQL * Python * SQL * Delta Lake * Azure Data Factory * Git / GitHub * Azure DevOps * MLflow * CI/CD Pipelines * MLOps / AgentOps * Enterprise AI & Machine Learning ## Description This is a Lead Data Scientist opportunity for an experienced technical leader who thrives at the intersection of Data Science, Machine Learning Engineering, and Data Engineering. The ideal candidate has successfully moved AI and machine learning solutions from experimentation into production and is passionate about building scalable, governed, enterprise-grade AI platforms. Working closely with Data Engineers, AI Engineers, and business stakeholders, you will lead the design, development, deployment, and operationalization of advanced analytics and AI solutions while helping establish best practices for MLOps, governance, and production AI. This is a highly visible opportunity to influence the organization's AI strategy while remaining hands-on with modern cloud technologies., * Lead the design, development, deployment, and operationalization of machine learning and AI solutions within Azure and Databricks environments. * Architect scalable data science workflows that transition models from research and experimentation into production. * Partner with Data Engineering teams to design robust ETL/ELT pipelines supporting enterprise AI initiatives. * Build and optimize machine learning pipelines using Python, PySpark, Spark SQL, Databricks, and Azure services. * Establish and improve MLOps and/or AgentOps practices, including model lifecycle management, monitoring, deployment automation, and governance. * Implement CI/CD pipelines utilizing Git, GitHub, Azure DevOps, or similar tooling to automate testing, deployment, and release management. * Collaborate with AI Engineers to develop and productionize Generative AI, LLM, and intelligent agent solutions where appropriate. * Drive best practices around AI governance, model management, reproducibility, security, and responsible AI. * Mentor junior Data Scientists and Engineers while providing technical leadership across cross-functional initiatives. * Translate complex business challenges into scalable AI and analytics solutions that can be reused across the enterprise. * Work closely with business stakeholders to prioritize high-impact opportunities and deliver measurable business value. * Influence architectural decisions and contribute to the long-term roadmap for enterprise AI capabilities., * Reports into a Data Science leadership organization working alongside AI Engineering and Data Engineering teams. * Serves as a technical leader on a growing enterprise AI team focused on production AI solutions. * Supports multiple business units through reusable AI and advanced analytics capabilities. * High-visibility role with significant influence on the organization's AI roadmap and digital transformation initiatives. * Preference for candidates located in or willing to relocate to the Houston area, with the ability to work onsite in a hybrid environment. * Strong preference for candidates interested in long-term conversion to a full-time role. Disclaimer: Brooksource, Medasource, and Calculated Hire are part of the Eight Eleven Group family of companies and operate under Eight Eleven Group, LLC. 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