Senior Data Scientist

A client in Spring, Tx is looking for a Sr. Data Scientist to join their Data Analytics Team. The Data Scientist must be proficient with Databricks and Azure AI. They would be joining a team of 3 other Data Scientist, helping with current and futuristic projects. This individual must be able to lead data-driven projects, guide strategic decisions, and provide strong mentorship to support junior team members and interns. This role will start as a 6-month contract with the goal to extend or convert to a full-time employee. It will require working a hybrid schedule, on-site Tuesday-Thursday. PREFERRED SKILLS AND EXPERIENCE • 5+ Years of Experience as a Data Scientist • Strong Communication and Leadership Skills • Bachelor's degree in data science, Information Systems, Computer Science, Engineering or other relevant field • Proficient in machine learning, data mining, statistical analysis, and applied AI methods using Databricks, Azure ML Skilled in developing scalable ML solutions and translating analytics into business impact • Advanced proficiency in Python, PySpark, SQL, and tools such as Jupyter, VS Code, and MLflow • Experience with database technologies and architectures including Delta Lake, Azure Data Lake, SQL Warehouses, and Synapse Analytics. • Hands-on experience with AutoML platforms such as Azure AutoML • Deep understanding of Azure Cloud resources, including Azure Machine Learning, Azure DevOps, Azure Cognitive Search, and Azure OpenAI Job Duties: • Apply advanced data science concepts to deliver data-driven digital offerings and insights using Databricks Lakehouse architecture. • Utilize modern machine learning methods and domain understanding to support the creation of new products and services, leveraging MLflow for experiment tracking and model lifecycle management. • Collaborate with data and analytics teams and cross-functional departments such as digital, services, class, and engineering to build scalable ML solutions and deliver actionable insights. • Write independent source code in Python, PySpark, and SQL, validate and test models, and use Databricks Feature Store for consistent feature reuse and governance. • Develop and deploy scalable and interpretable data products per business-defined requirements using Databricks Repos, Model Serving, and Azure Machine Learning.