Evangelos K.

Data Scientist

Greece

Trusted member since 2024

6 years of experience

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 View5 years

Data Science5 years

Azure4 years

Scikit-learn5 years

16+

Experience2

Senior Data Scientist

Accenture•

Information Technology (IT) and Services

Sep 2022 · 4y 1m

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.

Azure Blob storage

Data Science

Pandas

Scikit-learn

Data Analytics

Data Scientist

Propulsion Analytics•

Data Analytics

Aug 2019 - Aug 2022 · 3y

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.

Data Science

Keras

Pandas

Scikit-learn

Data Analytics

Engineering excellence

All Data Scientists who have applied to Proxify are scored from 0 to 300 on engineering excellence, one of the five parameters we evaluate. This score reflects engineering excellence only, based on interviews, take-home assignments, live coding sessions, and/or on-the-job performance reviews. The curve shows how all evaluated Data Scientists are distributed across that range, where our acceptance threshold for this parameter sits, and where Evangelos stands.