Green Key Resources
Data Solutions Architect
General Summary The Data Solutions Architect will play a pivotal role in advancing organizational data and artificial intelligence (AI) initiatives. Leveraging statistical analysis, machine learning (ML), and large language models (LLMs), this role focuses on extracting insights and supporting decision-making across diverse business operations and professional service practices. The architect will collaborate with innovation teams, technical resources, and stakeholders to design and implement data-driven solutions that enhance service delivery and operational efficiency. Staying current with emerging technologies and best practices, the Data Solutions Architect will integrate cutting-edge techniques into projects, offering a unique opportunity to shape the future of data and AI within the professional services sector.
Principal Duties and Responsibilities Partner with operational and practice teams to identify challenges and opportunities for workflow improvement. Translate complex domain logic into actionable data requirements and AI use cases. Design, build, and maintain scalable data pipelines and infrastructure to support AI and BI initiatives. Utilize SQL, Python, R, and other analytics tools to analyze, model, and visualize data trends. Collaborate with technology teams to refine and maintain data pipelines, warehouses, and databases. Develop tools and processes to transform raw data into user-friendly formats for self-service analytics. Apply advanced quantitative methods, including ML and NLP, to identify patterns and build predictive models. Design and deploy systems for applications such as text analysis, trend analysis, and predictive modeling. Craft, test, and refine prompts for LLMs to generate contextually accurate outputs tailored to research and drafting workflows. Deliver AI-driven solutions from proof of concept through production, addressing cross-functional and practice-specific needs. Continuously monitor advancements in AI, ML, and data science, integrating innovative technologies into organizational projects.
Job Specifications
Required Education Bachelors degree in Data Science, Computer Science, Engineering, or related fields.
Preferred Education Masters degree in a relevant discipline; coursework in deep learning, NLP, or information retrieval is highly valued.
Required Experience Minimum of 3 years of relevant experience, including at least 2 years in data engineering and data science roles.
Competencies Demonstrated expertise in data analytics and engineering with a strong focus on data modeling. Proficiency in statistical programming languages (Python, R) and database management (SQL). Hands-on experience with ML, NLP, and data visualization tools. Strong problem-solving and communication skills, with the ability to present complex data to non-technical audiences. Experience in professional services or related environments preferred.
General Summary The Data Solutions Architect will play a pivotal role in advancing organizational data and artificial intelligence (AI) initiatives. Leveraging statistical analysis, machine learning (ML), and large language models (LLMs), this role focuses on extracting insights and supporting decision-making across diverse business operations and professional service practices. The architect will collaborate with innovation teams, technical resources, and stakeholders to design and implement data-driven solutions that enhance service delivery and operational efficiency. Staying current with emerging technologies and best practices, the Data Solutions Architect will integrate cutting-edge techniques into projects, offering a unique opportunity to shape the future of data and AI within the professional services sector.
Principal Duties and Responsibilities Partner with operational and practice teams to identify challenges and opportunities for workflow improvement. Translate complex domain logic into actionable data requirements and AI use cases. Design, build, and maintain scalable data pipelines and infrastructure to support AI and BI initiatives. Utilize SQL, Python, R, and other analytics tools to analyze, model, and visualize data trends. Collaborate with technology teams to refine and maintain data pipelines, warehouses, and databases. Develop tools and processes to transform raw data into user-friendly formats for self-service analytics. Apply advanced quantitative methods, including ML and NLP, to identify patterns and build predictive models. Design and deploy systems for applications such as text analysis, trend analysis, and predictive modeling. Craft, test, and refine prompts for LLMs to generate contextually accurate outputs tailored to research and drafting workflows. Deliver AI-driven solutions from proof of concept through production, addressing cross-functional and practice-specific needs. Continuously monitor advancements in AI, ML, and data science, integrating innovative technologies into organizational projects.
Job Specifications
Required Education Bachelors degree in Data Science, Computer Science, Engineering, or related fields.
Preferred Education Masters degree in a relevant discipline; coursework in deep learning, NLP, or information retrieval is highly valued.
Required Experience Minimum of 3 years of relevant experience, including at least 2 years in data engineering and data science roles.
Competencies Demonstrated expertise in data analytics and engineering with a strong focus on data modeling. Proficiency in statistical programming languages (Python, R) and database management (SQL). Hands-on experience with ML, NLP, and data visualization tools. Strong problem-solving and communication skills, with the ability to present complex data to non-technical audiences. Experience in professional services or related environments preferred.