Kristin Abkemeier

About Kristin Abkemeier

Data scientist supporting U.S. Government agencies. Clearance information is available upon request.• Delivers end-to-end data science value chain, from executive communications and data visualization for decision support through data analysis and machine learning.• Technical expert with advisory experience and communications skills that target a range of audiences. Assessed and reported on multiple technologies and business models to support executive decision-making.• Completed the Data Science Specialization offered by Coursera and Johns Hopkins University to gain skills in data science using the R language, as well as other courses to learn Python. Versed in statistics, linear regression modeling, data visualization in Tableau and Power BI, natural language processing (NLP), machine learning, making data products using Shiny.TECHNICAL SKILLSLanguages: Python, R, C#, XML, JavaScript, Visual Basic, IDL, Fortran.Deep Learning: PyTorch, Tensorflow, Keras.Data Visualization & Design Tools: Tableau, Power BI, Adobe Illustrator, Photoshop, Shiny, Excel, PowerPoint.Data Analysis Tools: AWS SageMaker, Alteryx Designer, Jupyter Notebooks, Google Colab, statistics, regression modeling, machine learning. Web: ASP.NET MVC, HTML, CSS.Databases: SQL, Oracle, Microsoft Access.

Experience

1. Lead Data Scientist

   Booz Allen Hamilton

   Jan 2020 — Present

   Data Engineer and Scientist providing technical leadership and engineering for the U.S. Department of Defense (DoD). Deploying tools and physical science expertise for the climate change module within the Advana Analytics Platform to deliver actionable insights to inform decision making on clean energy and climate adaptation by the executive leadership in the Office of the Secretary of Defense. • Cloud, Big Data. Software development with ETL, Databricks, AWS Cloud, Python, PySpark and SQL, Big Data. Automating ETL pipelines with Databricks.• AWS Certified Cloud Practitioner, July 2021.• Provided program management support as a Technical SETA at the Intelligence Advanced Research Projects Activity (IARPA) supporting the SMART (Space-based Machine Automated Recognition Technique) program that is developing advanced machine learning (ML) techniques to identify anthropogenic and natural changes in land seen in satellite imagery.• Shepherded the SMART program from source selection of the performers, through the transition between program managers, to the official program kickoff.• Mastered deep learning concepts for computer vision (convolutional neural networks, or CNNs) and the packages TensorFlow 2.0 (using Keras) and PyTorch.

Education

• University of Chicago

  Ph.D., Physics

• Princeton University

  B.S.E., Electrical Engineering with Certificate in Engineering Physics, magna cum laude

• University of Chicago

  M.S., Physics

• University of Cambridge

  M. Phil., Physics

Skills

• Environmental Awareness
• Alternative Energy
• Market Analysis
• Cross-Functional Team Leadership
• Marketing Strategy
• Technology Analysis
• Environmental Policy
• Team Building
• Crm
• International Relations
• Renewable Energy
• Technology Policy
• Photovoltaics
• Technology Transfer
• Analysis
• Physics
• Project Implementation
• Strategy Development
• Program Management
• Cleantech
• Data Analysis
• Sustainable Energy
• Solar
• Nanotechnology
• Marketing Communications
• Solar Energy
• Energy Storage
• Technology Commercialization
• Business Strategy
• Climate Change
• Smart Grid
• Semiconductors
• Sustainable Development
• Electric Vehicles
• Proposal Writing
• Strategy
• Competitive Analysis
• Market Research
• Editing
• Batteries