AI/ML Data Analyst
Location: Dallas TX
Key Responsibilities
Data Preparation & Feature Engineering: Clean, preprocess, and structure massive, unstructured, or semi-structured datasets to make them ready for AI/ML model training.
Model Performance Evaluation: Analyze, visualize, and report on the performance metrics of predictive models and Generative AI agents, identifying data drift or anomalies.
Insight Generation & Dashboarding: Design and build advanced dashboards (Power BI / Tableau) to translate complex AI/ML outputs into strategic, plain-language stories for client stakeholders.
AI Governance & Quality Assurance: Validate data integrity, actively screen for algorithmic biases, and ensure all data processing complies with Deloitte’s Trustworthy AI™ framework.
Cross-Functional Collaboration: Translate complex business problems into specific data requirements, bridging the gap between non-technical client leaders and technical AI engineering teams.
Required Technical Skills
Programming & Scripting: Strong proficiency in Python (specifically Pandas, NumPy, Scikit-Learn) or R for data manipulation and analysis.
Database Management: Advanced SQL skills for querying complex, distributed databases and performing ETL (Extract, Transform, Load) operations.
Data Visualization: Mastery of Power BI or Tableview to build executive-ready reports.
AI/ML Familiarity: Solid understanding of machine learning workflows, data pipeline orchestration, and evaluation metrics (e.g., Precision, Recall, ROC-AUC, or LLM evaluation frameworks).
Cloud Ecosystems: Hands-on experience working with data inside cloud environments like AWS (S3, SageMaker), Azure (Synapse, Azure ML), or Google Cloud Platform (BigQuery).
Qualifications & Experience
Experience: 8 years of professional experience as a Data Analyst, Business Intelligence Analyst, or Junior Data Scientist, ideally within a management consulting or enterprise corporate environment.
Education: Bachelor’s degree in Data Analytics, Computer Science, Statistics, Mathematics, Economics, or a related quantitative field.
Soft Skills: Exceptional written and verbal communication skills. Since this is a client-facing, fully remote role, you must excel at running virtual workshops and presenting data narratives independently.
Nice-to-Have: Certifications in cloud data analytics (e.g., AWS Certified Data Analytics, Azure Data Analyst Associate).
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