Evangelos K.
Data Scientist
Evangelos er Data Scientist med fem års forretningsbakgrunn i oppstartsbedrifter og multinasjonale selskaper. Han spesialiserer seg i Python, PySpark, SQL, Azure Databricks og PowerBI, og utmerker seg i å utvikle prediktive modeller, lage ETL-pipeliner og utføre datakvalitetskontroller.
En av hans bemerkelsesverdige prestasjoner var å automatisere datakvalitetssjekker for et ledende drikkevareselskap, noe som betydelig forbedret påliteligheten til deres PowerBI-dashbord. Han har en mastergrad i forretningsanalyse.
Hovedekspertise
- Qlik View 5 år
- Data Science 5 år
- Azure 3 år
Andre kunnskaper
- Unix shell 2 år
- R (programming language) 2 år
- SAP ABAP 1 år
Utvalgt opplevelse
Arbeidserfaring
Senior Data Scientist
Accenture - 2 years 3 months
Data & AI (Products) - FMCG
- Customer segmentation using clustering techniques & data mining, enabling targeted efforts in many other projects.
- Data quality processes automation, industrialization and expansion to multiple markets for optimization of promotional strategies, improving consistency and reliability of data insights. (Raw-Curated/Datamesh)
- Reporting and enhancement of DQ checks, achieving great reduction in data errors, ensuring more reliable business decisions and enhanced the efficiency of data quality reporting, allowing business managers to quickly identify and address data issues.
- Entity resolution — Similarity algorithms —Ranking with classification. Improved the quality and richness of customer master data, leading to a more comprehensive understanding of customer behavior.
Teknologier:
- Teknologier:
- Data Science
- Scikit-learn
- Pandas
- Data Analytics
- Machine Learning
- Product
Data Scientist
Propulsion Analytics - 3 years
Propulsion Analytics is a product based company in the Maritime industry providing vessel and engine performance issues and predictions by utilizing vessel sensor data and creating digital twins and simulation algorithms using machine learning.
- Received great client feedback for developing and implementing innovative methods for vessel performance/fouling estimation and prediction for over 30 vessels using ML techniques and visualizations, saving millions to vessel owners by informed decisions regarding vessel routes and repairing events.
- ETL for vessel sensor data for 50+ vessels (1sec-5min frequencies) and tuning (hyperparameter optimization) and deployment of ML algorithms for ~30 vessels.
- Created unsupervised clustering algorithms for engine performance.
- Anomaly detection for time series data with ML techniques and PySpark for big data (queries, aggregations) and ad-hoc analysis.
- Product development.
Teknologier:
- Teknologier:
- Data Science
- Scikit-learn
- Keras
- Pandas
- Data Analytics
- Machine Learning
- Product
Utdannelse
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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