Advanced knowledge of data science, statistical analysis, machine learning, artificial intelligence, and advanced analytical methods.
Strong knowledge of Microsoft Fabric architecture and development, including semantic models, notebooks, and related analytical capabilities.
Advanced proficiency with SQL and Python for data transformation, analysis, modeling, and solution development.
Strong knowledge of Power BI semantic models and DAX, including model performance optimization and reusable measure design.
Working knowledge of generative AI, large language model concepts, conversational analytics, and enterprise AI solution patterns.
Experience with Git-based source control, Azure DevOps, pull requests, CI/CD, testing, and deployment practices.
Knowledge of data governance, lineage, metadata management, documentation, data quality, and analytical security concepts including row-level and object-level security.
Ability to identify complex problems, evaluate alternatives, and design scalable analytical and technical solutions.
Ability to communicate complex technical and analytical concepts to both technical and non-technical audiences.
Ability to work independently and collaboratively across Business Intelligence, Data Engineering, IT, leadership, and business teams.
Ability to manage multiple projects and priorities while maintaining technical quality and documentation standards.
Ability to train, mentor, and establish technical best practices for others.
Responsibilities
Collaborate with leadership and business units to identify high-value opportunities for advanced analytics, artificial intelligence, machine learning, and governed semantic solutions.
Design, develop, evaluate, deploy, and monitor statistical, predictive, prescriptive, machine learning, and artificial intelligence solutions that address business opportunities and operational challenges.
Develop AI solutions using structured and unstructured enterprise data and evaluate emerging AI technologies for responsible integration into business processes and analytical products.
Establish standards and best practices for AI development, evaluation, documentation, deployment, monitoring, explainability, and responsible use.
Design, develop, deploy, and maintain enterprise semantic models within Microsoft Fabric.
Transform governed Gold-layer data into analytics-ready semantic models by defining dimensional structures, relationships, measures, calculations, hierarchies, metadata, and business context.
Partner with Data Engineering teams to define and validate Gold-layer requirements necessary to support semantic models and downstream analytical solutions.
Ensure semantic models provide consistent business definitions, calculations, and context across Power BI, Microsoft Fabric, AI solutions, and other downstream consumers.
Optimize semantic models for performance, scalability, usability, security, and maintainability.
Implement modern development lifecycle practices for semantic models and analytical solutions, including Git-based source control, versioning, testing, peer review, CI/CD, and deployment across development, test, and production environments.
Partner with Business Intelligence professionals to ensure semantic models and analytical solutions effectively support enterprise reporting, self-service analytics, AI applications, and business decision-making.
Extract, analyze, identify, and assess qualitative and quantitative patterns, trends, anomalies, and relationships from large and complex data sets.
Prepare technical documentation and communicate analytical findings, model behavior, data requirements, and solution design to technical and business audiences.
Provide training and support and serve as a technical expert for semantic modeling, advanced analytics, and AI throughout the organization.
Maintain professional and technical knowledge by attending events, webinars, and educational opportunities.
Work safely at all times and adhere to all applicable safety policies; comply with all company policies, procedures, and standards.
Perform other duties as assigned.
The Data Scientist designs, develops, and implements advanced analytics, artificial intelligence (AI), and machine learning solutions that improve business decision-making and operational performance. The Data Scientist partners with business stakeholders, Business Intelligence professionals, and Data Engineering teams to translate business requirements into scalable analytical solutions. The role develops and maintains data assets, advanced analytical models, AI solutions, and supporting data transformations while establishing technical standards and best practices for analytics and AI development.
The incumbent in this position is expected to model the following practices on a daily basis:
Demonstrate alignment with the company's mission and core business values;
Collaborate with key internal/external resources;
Participate in ongoing self-development.
Models, promotes, reinforces, and rewards the consistent use of HOLT’s Values Based Leadership (VBL) tools, models, and processes to ensure alignment with our Vision, Values, and Mission
Collaborates with leadership and business units to identify high-value opportunities for advanced analytics, artificial intelligence, machine learning, and governed semantic solutions
Designs, develops, evaluates, deploys, and monitors statistical, predictive, prescriptive, machine learning, and artificial intelligence solutions that address business opportunities and operational challenges
Develops AI solutions using structured and unstructured enterprise data and evaluates emerging AI technologies for responsible integration into business processes and analytical products
Establishes standards and best practices for AI development, evaluation, documentation, deployment, monitoring, explainability, and responsible use
Designs, develops, deploys, and maintains enterprise semantic models within Microsoft Fabric
Transforms governed Gold-layer data into analytics-ready semantic models by defining dimensional structures, relationships, measures, calculations, hierarchies, metadata, and business context
Partners with Data Engineering teams to define and validate Gold-layer requirements necessary to support semantic models and downstream analytical solutions
Ensures semantic models provide consistent business definitions, calculations, and context across Power BI, Microsoft Fabric, AI solutions, and other downstream consumers
Optimizes semantic models for performance, scalability, usability, security, and maintainability
Implements modern development lifecycle practices for semantic models and analytical solutions, including Git-based source control, versioning, testing, peer review, CI/CD, and deployment across development, test, and production environments
Partners with Business Intelligence professionals to ensure semantic models and analytical solutions effectively support enterprise reporting, self-service analytics, AI applications, and business decision-making
Extracts, analyzes, identifies, and assesses qualitative and quantitative patterns, trends, anomalies, and relationships from large and complex data sets
Prepares technical documentation and communicates analytical findings, model behavior, data requirements, and solution design to technical and business audiences
Provides training and support and serves as a technical expert for semantic modeling, advanced analytics, and AI throughout the organization
Maintains professional and technical knowledge by attending events, webinars, and educational opportunities
Works safely at all times and adheres to all applicable safety policies; complies with all company policies, procedures, and standards
Performs other duties as assigned
Advanced knowledge of data science, statistical analysis, machine learning, artificial intelligence, and advanced analytical methods
Strong knowledge of Microsoft Fabric architecture and development, including semantic models, notebooks, and related analytical capabilities
Advanced proficiency with SQL and Python for data transformation, analysis, modeling, and solution development
Strong knowledge of Power BI semantic models and DAX, including model performance optimization and reusable measure design
Working knowledge of generative AI, large language model concepts, conversational analytics, and enterprise AI solution patterns
Experience with Git-based source control, Azure DevOps, pull requests, CI/CD, testing, and deployment practices
Knowledge of data governance, lineage, metadata management, documentation, data quality, and analytical security concepts including row-level and object-level security
Ability to identify complex problems, evaluate alternatives, and design scalable analytical and technical solutions
Excellent verbal, written, communication, presentation, interpersonal, and customer service skills. With the ability to communicate complex technical and analytical concepts to both technical and non-technical audiences
Ability to work independently and collaboratively across Business Intelligence, Data Engineering, IT, leadership, and business teams
Ability to manage multiple projects and priorities while maintaining technical quality and documentation standards
Ability to train, mentor, and establish technical best practices for others