Daniel Karcz

Strong technical background with the ability to proactively identify and mitigate technical risks throughout delivery life-cycle. An operator that executes on high priority enterprise level initiatives, influences across organizations and drives the implementations of technical strategies. Specifically, partnering closely with stakeholders, product engineers, data scientists and other cross functional teams to create roadmaps, scope programs aligning them with business priorities, define milestones and success metrics, and build scalable, secure, reliable, efficient products and platforms.

Data Scientist with 13 years of full time professional work experience.

Core competencies include: machine learning, statistical modeling, data mining, data engineering, mathematics, database management (relational/graph/non-relational), cloud analytics, data pipeline workflows, developing interactive dashboards, project management, and customer relationships.

NASA Jet Propulsion Laboratory (JPL) – Complex Event Processing & ML
Research Data Science Internship

https://​www​.iit​.edu/​n​e​w​s​/​d​a​t​a​-​s​c​i​e​n​c​e​-​s​t​u​d​e​n​t​-​s​p​e​n​t​-​s​u​m​m​e​r​-​k​e​e​p​i​n​g​-​n​a​s​a​-​c​o​n​n​e​c​t​e​d​-​space

The Deep Space Network is NASA’s international array of giant radio antennas that
supports interplanetary spacecraft missions, plus a few that orbit Earth.  Project goals completed: uplink and downlink signal anomaly fault detection and isolation due to weather events, implementation of supervised machine learning algorithms to classify signal loss thresholds (“Out of Lock”, ​“Normal”), and Integration of classification algorithms into Complex Event Processing framework.