Led groundbreaking projects applying advanced statistical techniques & ML to analyze big cosmic datasets. My innovative methods advanced our understanding of cosmic large-scale structures & demonstrated significant potential for improving data-driven models in various fields.
2011 - 2015
Ph.D. in Astrophysics, Ludwig-Maximilians-Universität München
PROFESSIONAL SUMMARY:
Innovative Data Scientist with 8+ years of experience spanning energy sector, astrophysics, & big data analytics. Expert in developing & implementing ML models, ETL pipelines, & advanced statistical analyses using Python, SQL, cutting-edge data science libraries & CI/CD practices. Proven track record in anomaly detection, & operational automation for SaaS products. Adept at manipulating complex, high-volume data & collaborating with cross-functional teams to build scalable, data-driven solutions that enhance product development, optimize operations, & improve customer experiences. Demonstrated ability in project management & stakeholder engagement in B2B SaaS environments. Eager to establish & lead an impactful AI practice, leveraging cutting-edge technologies to drive strategic decision-making & innovation while ensuring high data quality & accuracy.
Technical Skills:
Problem-Solving Skills:
Developed algorithms improving anomaly detection accuracy, solving complex data challenges & enhancing operational efficiency in energy sector.
Adaptability:
Quickly adapted to diverse data formats & quality issues from various clients, streamlining processes to enhance project efficiency.
Curiosity & Continuous Learning:
Continuously explored new ML techniques & data processing methods, enhancing the robustness & efficiency of anomaly detection systems.
Communication Skills:
Effectively conveyed technical insights in stakeholder meetings, translating complex data analyses into actionable business strategies.
Leadership & Team Collaboration:
Led the development of robust ETL pipelines, fostering team collaboration, & enabling efficient project delivery across multiple high-impact projects.
Business Acumen:
Leveraged data science methodologies to optimize energy efficiency & reduce CO2 emissions & operational costs, aligning with broader goals of SaaS company & its client.
Led groundbreaking projects applying advanced statistical techniques & ML to analyze big cosmic datasets. My innovative methods advanced our understanding of cosmic large-scale structures & demonstrated significant potential for improving data-driven models in various fields.
2011 - 2015
Ph.D. in Astrophysics, Ludwig-Maximilians-Universität München
PROFESSIONAL SUMMARY:
Innovative Data Scientist with 8+ years of experience spanning energy sector, astrophysics, & big data analytics. Expert in developing & implementing ML models, ETL pipelines, & advanced statistical analyses using Python, SQL, cutting-edge data science libraries & CI/CD practices. Proven track record in anomaly detection, & operational automation for SaaS products. Adept at manipulating complex, high-volume data & collaborating with cross-functional teams to build scalable, data-driven solutions that enhance product development, optimize operations, & improve customer experiences. Demonstrated ability in project management & stakeholder engagement in B2B SaaS environments. Eager to establish & lead an impactful AI practice, leveraging cutting-edge technologies to drive strategic decision-making & innovation while ensuring high data quality & accuracy.
Technical Skills:
Problem-Solving Skills:
Developed algorithms improving anomaly detection accuracy, solving complex data challenges & enhancing operational efficiency in energy sector.
Adaptability:
Quickly adapted to diverse data formats & quality issues from various clients, streamlining processes to enhance project efficiency.
Curiosity & Continuous Learning:
Continuously explored new ML techniques & data processing methods, enhancing the robustness & efficiency of anomaly detection systems.
Communication Skills:
Effectively conveyed technical insights in stakeholder meetings, translating complex data analyses into actionable business strategies.
Leadership & Team Collaboration:
Led the development of robust ETL pipelines, fostering team collaboration, & enabling efficient project delivery across multiple high-impact projects.
Business Acumen:
Leveraged data science methodologies to optimize energy efficiency & reduce CO2 emissions & operational costs, aligning with broader goals of SaaS company & its client.