Evangelos K.

Data Scientist

Evangelos is a Data Scientist with five years of commercial experience in startups and multinational companies. Specializing in Python, PySpark, SQL, Azure Databricks, and PowerBI, he excels in developing predictive models, creating ETL pipelines, and conducting data quality checks.

One of his standout achievements was automating data quality checks for a leading beverage company, which significantly improved the reliability of their PowerBI dashboards. He possesses a masters degree in business analytics.

Main expertise

  • Qlik View
    Qlik View 5 years
  • Data Science 5 years
  • Azure
    Azure 3 years

Other skills

  • Unix shell 2 years
  • R (programming language)
    R (programming language) 2 years
  • SAP ABAP
    SAP ABAP 1 years
Evangelos

Evangelos K.

Greece

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Selected experience

Employment

  • Senior Data Scientist

    Accenture - 3 years

    • Performed customer segmentation using clustering techniques and data mining, which enabled targeted efforts in various projects.
    • Automated, industrialized, and expanded data quality processes across multiple markets to optimize promotional strategies, improving consistency and reliability of data insights (Raw-Curated/Datamesh).
    • Reported on and enhanced data quality checks, significantly reducing data errors, ensuring more reliable business decisions, and increasing the efficiency of data quality reporting, allowing business managers to quickly identify and address data issues.
    • Applied entity resolution techniques including similarity algorithms and ranking with classification, improving the quality and richness of customer master data and leading to a more comprehensive understanding of customer behavior.

    Technologies:

    • Technologies:
    • Data Science
    • Scikit-learn Scikit-learn
    • Pandas Pandas
    • Data Analytics
    • Machine Learning Machine Learning
    • Product

  • Data Scientist

    Propulsion Analytics - 3 years

    • Received excellent client feedback for developing and implementing innovative methods for vessel performance and fouling estimation and prediction for over 30 vessels using ML techniques and visualizations, which saved millions for vessel owners by enabling informed decisions on vessel routes and repair events.
    • Performed ETL on vessel sensor data for more than 50 vessels (with frequencies ranging from 1 second to 5 minutes), tuned (hyperparameter optimization), and deployed ML algorithms for approximately 30 vessels.
    • Created unsupervised clustering algorithms to analyze engine performance.
    • Conducted anomaly detection on time series data using ML techniques and PySpark for big data processing, including queries, aggregations, and ad-hoc analysis.
    • Participated in product development activities.

    Technologies:

    • Technologies:
    • Data Science
    • Scikit-learn Scikit-learn
    • Keras Keras
    • Pandas Pandas
    • Data Analytics
    • Machine Learning Machine Learning
    • Product

Education

  • MSc.Business Analytics

    Athens University of Economics and Business · 2018 - 2020

  • BSc.Economics

    National and Kapodistrian University of Athens · 2010 - 2015

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