Professional Statement

Passionate about turning complex data into practical, high-impact solutions, I specialize in bridging machine learning, distributed computing, and hybrid cloud systems. With a strong foundation in mathematics, statistics, and software design, I lead teams building scalable ML pipelines in on-prem, cloud, and hybrid environments, enabling innovation and transformation in operations.

Core Skills

• Machine & Statistical Learning: Forecasting, Time-Series Analysis, Generalized Additive Mixed Models, NLP-based Clustering
• Technologies: Apache Spark, Kubeflow Pipelines, Vertex AI, Azure ML, Hadoop, Docker, Kubernetes
• Programming Languages: Python, Scala, Java, R
• Leadership: Project Planning, Team Enablement, Mentorship, Cross-functional Collaboration, Enterprise Initiatives
• Cloud Systems: GCP, Azure, Hybrid Cloud Architecture, and Custom Vendor Solutions

Experience

Principal Data Scientist

Target | April 2025 - Present

• Lead strategic initiatives to modernize ML infrastructure, focusing on MLOps and cloud-native solutions.
• Architected and implemented the migration of a major enterprise forecasting product to Kubeflow Pipelines on Vertex AI.
• Designed frameworks to accelerate product development across data science teams, promoting enterprise adoption of ML at scale.
• Developed and executed onboarding and training strategies for data scientists transitioning to cloud-native technologies.
• Cyber security champion for team of 60+ data scientists. Actively addressing security concerns, mitigating vulnerabilities, and hosting a learning series to build a culture of cyber sercurity awareness

Technologies Used: Vertex AI, Kubeflow, Docker, Kubernetes

Lead Data Scientist

Target | June 2022 - April 2025

• Led high-impact data science initiatives, driving forecasting solutions that shaped Target’s operational strategy.
• Delivered the No History Forecast (NHF) model and Demand Forecast Evaluation Framework, enhancing decision-making processes.
• Created DFELite, a framework reducing model evaluation times from 20 hours to 15 minutes, boosting iteration speed.
• Focused on communication to bridge technical solutions with business needs, influencing stakeholders and non-technical teams.
• Mentored junior data scientists and fostered a culture of continuous learning.
• Cyber security champion for team of 60+ data scientists. Implemented solutions to bring Target’s forecasting group into compliance with enterprise product security goals.

Technologies Used: Apache Spark, Python, R, Scala, Hadoop

Senior Data Scientist

Target | July 2021 - June 2022

• Developed new digital item forecasting models for inventory positioning and planning.
• Rewrote forecasting inference engine in Scala, reducing runtime from several hours to 45 minutes.
• Implemented algorithms that improved accuracy in forecasting across departments, supporting global operations.
• Created internal tools for model testing and comparison, enhancing model validation and deployment.

Technologies Used: Apache Spark, Scala, Python, Hadoop, R

Senior Data Scientist

Ecolab | July 2020 - July 2021

• Led the development of Ecolab’s first enterprise forecasting system, optimizing the supply chain for bulk chemistry.
• Worked across various domains, developing models for time-series forecasting, signal classification, and computer vision.
• Contributed to patented innovation projects, advancing Ecolab’s technical capabilities.
• Provided technical leadership in MLOps across cloud and on-prem platforms, deploying models and interactive dashboards with Flask.

Technologies Used: Python, Java, Iguazio, MLRun, Azure ML, Kubeflow, Flask

Data Scientist

Ecolab | May 2019 - July 2020

• Built and deployed models for forecasting, classification, and recommendations across diverse industries.
• Created automation pipelines using Azure and Kubeflow, optimizing model training and predictions.
• Worked with cross-functional teams to explore new data science opportunities, delivering actionable insights.

Technologies Used: Python, Azure ML, Flask, TensorFlow, Xamerin

Education

PhD in Mathematics

University of Minnesota
Dissertation: Invariant Euler-Lagrange Equations for Variational Problems over Framed Curves in 2D/3D

• Focused on the application of mathematical theory to solve physics-related problems using Lie theory.
• Developed a Python library for symbolic calculations in differential geometry.

MSc in Mathematics

Minnesota State University, Mankato
Thesis: Pompeiu Problem for Line Segments in the Plane

• Proved new results on the Pompeiu property for integrals over curves in the plane.

BSc in Mathematics, Physics, and Chemistry

University of South Dakota
Triple major: Mathematics, Physics, Chemistry

• Developed strong quantitative and analytical skills through rigorous coursework and lab work across all three disciplines.

Selected Projects

• Real-Time Interactive Forecasting: Planned and designed a new forecasting system for pre-season and in-season forecasting, improving planning and strategy.
• DFE-Lite: An inernally published R library that provides a high performance framwork for training generalized additive mixed models for demand forecasting and other use cases.
• DFE Measurement Library: An internally published python library for measuring systems of forecasting model (as opposed to individual models).
• Demand-Based Store Clustering: Led the design of algorithms that optimized model strucutre for forecasting based on demand similarity profiles.
• No History Models: Led the design and implementation of a system to provide better forecasts for items with no sales history (cold start problem).
• Short History Digital Models: Implemented new forecasting models for digital items with short history.

Key Strengths

• Leadership: Leads cross-functional teams and mentors junior scientists.
• Communication: Bridged the gap between data science and non-technical business teams.
• Elevate: Work across teams to elevate skills and impact of data scientists.
• Impact: Delivered production systems that transformed decision-making and accelerated product development.