Evangelos K.
Data Scientist
Evangelos er data scientist med fem års kommerciel erfaring fra startups og multinationale virksomheder. Med speciale i Python, PySpark, SQL, Azure Databricks og PowerBI udmærker han sig ved at udvikle prædiktive modeller, skabe ETL-pipelines og udføre datakvalitetstjek.
En af hans største bedrifter var at automatisere datakvalitetskontroller for en førende drikkevarevirksomhed, hvilket forbedrede pålideligheden af deres PowerBI-dashboards betydeligt. Han har en kandidatgrad i forretningsanalyse.
Hovedekspertise
- Qlik View 5 år
- Data Science 5 år
- Azure 3 år
Andre færdigheder
- Unix shell 2 år
- R (programming language) 2 år
- SAP ABAP 1 år
Udvalgt oplevelse
Beskæftigelse
Senior Data Scientist
Accenture - 2 flere år 3 måneder
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 flere år
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
Uddannelse
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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