Architect, Data Science Resume

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Architect, Data Science Resume Jaylen Callahan Architect, Data Science (312) 555-0187 jaylen.callahan@example.com linkedin.com/example/jaylencallahan Chicago, Illinois 60611 STRENGTHS Business-Value Framing Turns model plans into ROI, revenue, margin, and cost measures. A clear scorecard helped executives choose delivery priorities. Client Partnership Builds trust during uncertain discovery work. Client teams returned for practical answers when scope, risk, or pricing shifted. Platform Architecture Shapes governed Databricks pipelines from prototype through production. Teams gained a repeatable path for reliable delivery and support. Executive Communication Makes model trade-offs understandable without flattening technical nuance. Workshop conversations became decisions, not lengthy status updates. Team Enablement Leaves client teams with runbooks, ownership practices, and confidence. Knowledge transfer continued after project delivery ended. SKILLS Python SQL Databricks Unity Catalog MLflow Delta Tables MLOps Hugging Face LangChain DSPy Forecasting Anomaly Detection Recommendation Systems Computer Vision Causal Inference LANGUAGES English Native 40 Spanish Intermediate 20 MY CAREER 10.4 Years Principal Data Science Architect at Pinnacle Meridian Group (3 Years) Senior Data Science Consultant at Harborline Data Partners (2.6 Years) Data Science Lead at Cedar Peak Consulting (2.5 Years) Data Scientist at Blue Ridge Analytics (2.3 Years) SUMMARY Data Science Architect with 10+ years delivering enterprise AI and machine learning solutions, including large-scale deployments and more than eight years advising clients, executives, and delivery teams. Builds secure Databricks platforms and maintainable ML pipelines across data analysis, feature engineering, model training, deployment, and MLOps. Brings hands-on depth in Python, SQL, forecasting, anomaly detection , recommendation systems , computer vision, risk modeling, mathematical optimization , revenue management, price modeling, and causal inference. Leads technical scoping, feasibility reviews, Statements of Work , pricing, prototypes, and production delivery. Enjoys helping teams make sound decisions, adopt practical AI workflows, and sustain results through workshops, writing, and clear executive communication. EXPERIENCE Principal Data Science Architect Pinnacle Meridian Group September 2023 - Present Chicago, Illinois Leads consulting strategy across retail, manufacturing, and energy engagements. Directs Data Scientists, Data Engineers, and ML Engineers through architecture, presales, delivery, governance, and client enablement. Connects platform choices with revenue, margin, service, cost, and adoption outcomes. Set AI strategy across seven client engagements, linking Databricks roadmaps with revenue, margin, service, and cost goals. Built governed lakehouse pipelines with Unity Catalog , Delta Tables , and MLflow for forecasting and recommendations. Directed Data Scientists, Data Engineers, and ML Engineers through validation, deployment, monitoring, and operational handoff. Shaped Statements of Work, feasibility reviews, pricing options, and pitches for complex client proposals. Established code reviews, experiment tracking, and release controls that improved repeatability across Python and SQL solutions. Led executive workshops on causal inference , price modeling , LLM adoption, and operational risk for C-suite sponsors. Senior Data Science Consultant Harborline Data Partners January 2021 - August 2023 Atlanta, Georgia Delivered client-facing revenue management and AI programs for multi-region retail organizations. Combined causal inference, forecasting, optimization, Databricks engineering, LLM prototyping, presales, and enablement sessions into practical operating solutions. Delivered retail price optimization using causal inference, demand forecasting , and mathematical optimization for weekly decisions. Built Databricks pipelines with Delta Tables, MLflow, and Unity Catalog controls across transaction and inventory data. Created anomaly detection and recommendation services with Python and SQL, supported by backtesting and calibration reviews. Prototyped document classification and analyst question-answering workflows with Hugging Face , LangChain, and commercial LLM APIs . Presented solution economics, delivery risks, scope, and pricing assumptions to finance, procurement, and executive audiences. Facilitated client workshops covering runbooks, feature definitions, monitoring thresholds, and operational ownership practices. Data Science Lead Cedar Peak Consulting June 2018 - December 2020 Denver, Colorado Led predictive analytics workstreams for manufacturing and utilities clients. Guided a four-person delivery team through discovery, experimentation, architecture, validation, technical pitches, production readiness, and stakeholder adoption. Translated equipment, demand, and service questions into deployable forecasting and anomaly detection products. Implemented Python, SQL, and Databricks pipelines with feature engineering , scheduled scoring, and analyst review workflows. Guided four-person teams through experiment design, peer review, model cards, and production readiness checks. Built computer vision proof of concept with labeled images, model evaluation, and plant-floor acceptance testing. Estimated cloud dependencies, integration effort, staffing, and delivery phases for client proposals and technical pitches. Published practical notes on model drift, causal inference, and responsible experimentation for client-facing consultants. Data Scientist Blue Ridge Analytics January 2016 - May 2018 Raleigh, North Carolina Developed predictive analytics for consumer and media clients, connecting behavioral data with planning decisions. Supported dataset preparation, model evaluation, Databricks migration, anomaly alerting, client communication, and implementation handoffs. Developed demand forecasting and recommendation models with Python , SQL, and reproducible notebooks for client planning. Prepared sales, digital activity, and service datasets, resolving quality issues and documenting feature lineage. Evaluated model candidates through cross-validation, backtesting, and error segmentation for sponsor review. Created anomaly detection service with calibrated thresholds, alert guidance, and an engineering handoff package. Converted batch transformations into Delta Tables during Databricks migration, recording experiments in MLflow . Presented model limitations and practical use cases during client working sessions and implementation reviews. PROJECTS Retail Revenue Optimization Lab 2024 Connected causal inference, demand forecasting, price modeling, and mathematical optimization into a reusable decision workflow for commercial planning teams. Enterprise LLM Analyst Assistant 2023 Combined Hugging Face, LangChain, DSPy, and commercial LLM APIs within a governed prototype for document research and analyst questions. Computer Vision Quality Pilot 2020 Created an image-based inspection prototype with evaluation checkpoints, operational acceptance criteria, and a practical handoff plan for plant teams. LEADERSHIP & AWARDS Databricks Lakehouse Innovation Award, 2025 Applied Analytics Excellence Award, Harborline Data Partners, 2022 Graduate Research Fellowship, North Carolina State University, 2014 EDUCATION Master's Degree in Applied Statistics North Carolina State University GPA: 4.0 2015 Raleigh, North Carolina Coursework: Statistical Modeling, Causal Inference, Machine Learning, Experimental Design Bachelor's Degree in Economics University of Georgia GPA: 3.8 2013 Athens, Georgia Coursework: Econometrics, Optimization, Revenue Management, Quantitative Analysis CERTIFICATIONS Databricks Certified Machine Learning Professional 2024 AWS Certified Machine Learning - Specialty 2023 Databricks Certified Data Engineer Professional 2022 TECHNICAL SKILLS Programming and Querying: Python, SQL, Jupyter, pandas Databricks Platform: Databricks, Unity Catalog, Delta Tables MLOps and Lifecycle: MLflow, model monitoring, model registry LLM Tooling: Hugging Face, LangChain, DSPy Cloud Platforms: AWS, Azure, GCP Predictive Modeling: Forecasting, anomaly detection, recommendation systems Advanced Analytics: Computer vision, risk modeling, causal inference Optimization and Pricing: Mathematical optimization, revenue management, price modeling Data Engineering: Feature engineering, ETL, batch pipelines Validation Methods: Cross-validation, backtesting, holdout analysis Delivery Methods: Rapid prototyping, proofs of concept, technical presales Client Deliverables: Statements of Work, feasibility assessments, pricing models SKILLS Python SQL Databricks Unity Catalog MLflow Delta Tables MLOps Hugging Face LangChain DSPy Forecasting Anomaly Detection Recommendation Systems Computer Vision Causal Inference PROFESSIONAL AFFILIATIONS Conference Speaker, Data Platforms and AI Forum, 2025 Contributor, Internal Responsible AI Practice, 2021 - Present Mentor, Analytics Community of Practice, 2019 - 2023 LANGUAGES English (Native) Spanish (Intermediate) ADDITIONAL INFORMATION Work Status : Authorized to work in United States. No sponsorship required. ADDITIONAL INFORMATION Work Status : Authorized to work in United States. No sponsorship required. REFERENCES AVAILABLE ON REQUEST

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