Data Solutions Architect

Overview

• Contribute to data-driven innovations within the legal industry, leveraging AI and ML technologies to enhance workflows and operational efficiency.
• Collaborate with cross-functional teams to identify opportunities for improving legal processes and implementing advanced data solutions.
• Design and maintain scalable data pipelines and infrastructure supporting AI and business intelligence applications.
• Utilize statistical programming languages and tools to analyze, model, and visualize data insights.
• Stay updated with advancements in AI, ML, and data science to integrate cutting-edge technologies into projects.
• Develop self-service analytics tools and processes for transforming raw data into actionable insights.
• Apply advanced quantitative research methods to identify trends and develop predictive models.
• Collaborate with technology teams to refine data structures and warehouses for optimal performance.
• Craft and refine prompts for large language models tailored to legal research and drafting workflows.

Key Responsibilities & Duties

• Identify business challenges and opportunities to enhance legal workflows and processes through data solutions.
• Translate complex legal domain requirements into actionable data and AI use cases.
• Design and implement scalable data pipelines and infrastructure for AI and BI applications.
• Analyze and model data using SQL, Python, R, and visualization tools to extract insights.
• Collaborate with technology teams to maintain essential data structures and warehouses.
• Develop tools for transforming raw data into user-friendly views for analytics purposes.
• Apply ML and NLP techniques to analyze data trends and develop predictive models.
• Design and deploy analyses and systems for applications like text analysis and predictive modeling.
• Stay current with AI and data science advancements to integrate innovative technologies into projects.

Job Requirements

• Bachelor’s degree in Data Science, Computer Science, Engineering, or related fields required; Master’s degree preferred.
• Minimum 3 years of relevant experience, including 2 years in data engineering and data science roles.
• Proficiency in Python, R, SQL, and data visualization tools.
• Hands-on experience with ML, NLP, and advanced quantitative research methods.
• Strong problem-solving and communication skills for presenting complex data to non-technical audiences.
• Experience in legal or professional services environments preferred.
• Ability to design and implement data-driven solutions addressing cross-functional needs.
• Familiarity with large language models and crafting effective prompts for tailored outputs.
• Knowledge of current AI and data science trends and technologies.