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Profileimage by Anonymous profile, Data Scientist, Data Engineer, Business Intelligence, Data Warehousing, Big Data
Dublin
not available until 06/30/2024

Last update: 01.04.2024

Data Scientist, Data Engineer, Business Intelligence, Data Warehousing, Big Data

Graduation: Mathematician
Hourly-/Daily rates: show
Languages: German (Native or Bilingual) | English (Full Professional) | French (Elementary)

Keywords

Attachments

TMI_280223.pdf
TMI_280223.pdf

Skills

I am a competent Senior Data Scientist with excellent communication and interpersonal skills, together with a proven track record of technical skills. I have over 20 years of experience turning data into meaningful information on large-scale installations.

Available for a freelance position in Europe, onsite and/or remote. Price will be individual and based on the requirements.

Azure Synapse, Azure Data Factory, RDBMS, Oracle, PostgreSQL, SQL, PL/SQL, Python, Pandas, Tesnorflow, Keras, SciKit-Learn, Dash, NoSQL, Neo4J, MongoDB, Big Data, Apache Spark, Cloud platforms, Azure, AWS, Frontends, Power BI, Jupyter Notebook, cloud, web-based, APIs, feature engineering, machine learning, Data Science, DWH, Data Warehouse, data protection, ETL, Datamart , Business Intelligence
 

Project history

05/2022 - Present
Data Scientist | Data Engineer | Architect
Interantional logistics company (Transport and Logistics, 250-500 employees)
Migration and significant extension of the existing enterprise reporting solution into a cloud-based analytics platform. 

The cloud-based analytics platform includes modules for data ingestion, delta calculation, and data quality and metadata management components to provide a single point of truth for various consumers to build their business-specific data analytics on.
  • High-level design and architecture of the overall system
  • Conceptual orchestration of the module classes
  • Definition of internal and external interfaces
  • Implementation of modules
  • Design and implementation of a central repository
  • Implementation of service encapsulation and orchestration
  • Selection and preparation of test data sets
  • Iteration management: definition, execution, evaluation
  • Definition and evaluation of functional/non-functional requirements
  • Development of technical conception derived from requirements
  • Creation of data pipelines for structured data (ETL)
  • Conception and creation of data models
  • Creation of frontends for different stakeholders
  • Process automation and CI/CD

Techstack: Azure Synapse, Azure Blob Storage, Azure SQL Server, MS PowerBI, Azure Key Vault, MariaDB, SQL, python, pandas, MS Visual Studio Code, Data Vault 2.0, Jira, Confluence, GIT, Azure DevOps
08/2021 - 04/2022
Data Scientist | Data Engineer | Architect
International insurance company (Insurance, >10.000 employees)
Architecture, design and implementation of a globally organized data platform to collect and curate data from the subsidiaries in different countries. 

The cloud based data platform contains modules for ingestion, delta calculation as well as data quality and meta data management components to provide a single point of truth for different consumers to build their business specific data analysis on top of it. 

•    High-level design and architecture of the overall system
•    Conceptual orchestration of the module classes
•    Definition of internal and external interfaces
•    Implementation of modules
•    Design and implementation of a central repository
•    Implementation of service encapsulation and orchestration
•    Selection and preparation of test data sets
•    Iteration management: definition, execution, evaluation
•    Definition and evaluation of functional/non-functional requirements
•    Development of technical conception derived from requirements
•    Creation of data pipelines for structured data (ETL)
•    Conception and creation of data models
•    Creation of frontends for different stakeholders
•    Process automation and CI/CD

Techstack: Azure Data Factory, Azure Blob Storage, Azure Database for PostgreSQL, Azure Databricks Service, MS PowerBI, SQL, python, pandas, MS Visual Studio Code, Data Vault 2.0, Jira, Confluence, GIT, Azure DevOps
03/2021 - 08/2021
Data Scientist | Data Engineer
Company for digital transformation solutions (Internet and Information Technology, 500-1000 employees)
Successful implementation proof of concept for the use of Artificial Intelligence in the field of condition monitoring and predictive maintenance for IOT based devices, mainly large stationary and mobile machines.

•    Definition and evaluation of functional/non-functional requirements
•    ETL: Creation of data pipelines for structured data (timeseries)
•    Data exploration and analysis
•    Data preparation and feature engineering
•    Creation, evaluation and integration of machine learning models
•    Design and build of the analytic core structure
•    Design of data drift detection modules
•    Creation of frontends for visualization of the results
•    Process automation and CI/CD
•    Rapid Prototyping
•    Communication and Involvement of all stakeholders
•    Presentation of intermediate results
•    Overall system architecture

Techstack: python, pandas, sklearn, tensorflow, keras, sktime, jupyter, tsfresh, MS Visual Studio Code, prophet, matplotlib, dash, Azure Blob Storage, Azure Virtual Machines, Azure Machine Learning, Azure SQL Database
09/2019 - 03/2021
Data Scientist | Data Engineer | CTO and Co-Founder
Startup digital platform for sustainable development (Internet and Information Technology, < 10 employees)
Creating a cloud based and AI driven digital platform to align a specific industry to the Sustainable Development Goals (SDGs) of the UN as a spearhead organization for next gen companies.

•    Definition and evaluation of functional/non-functional requirements
•    ETL: Creation of data pipelines for structured and unstructured data
•    Data acquisition from web-based sources and-third party APIs
•    Data exploration and analysis
•    Data preparation and feature engineering
•    Creation, evaluation and integration of machine learning models
•    Design and build of the analytic core structure
•    Creation of frontends for different stakeholders
•    Process automation and CI/CD
•    Rapid Prototyping
•    Communication and Involvement of all stakeholders
•    Presentation of intermediate results
•    Overall system architecture
•    Planning, Budgeting, Teamlead

Techstack: SQL, python, pandas,  tensorflow, keras, sklearn, sktime, jupyter, atom, MS Visual Studio Code, beautifulsoup, selenium, prophet, bert, spacy, folium, rasterio, gdal, matplotlib, dash, pillow, geopandas, Azure Databricks, Azure EH4Kafka, Azure HDInsight, Azure Blob Storage, Azure Virtual Machines, Azure API Apps, Azure Functions, Azure Database for PostgreSQL, Azure Machine Learning, Azure logic Apps, PowerBI
10/2017 - 09/2019
Data Scientist | Data Engineer | Architect
Startup AI Service Platform (Internet and Information Technology, 10-50 employees)
Development of a platform for the use of microservice based machine learning models in operative IT environments and the business processes integrated in them.

•    High-level design of the overall system
•    Conceptual orchestration of the module classes
•    Definition of internal and external interfaces
•    Implementation of modules
•    Design and implementation of a central repository
•    Implementation of service encapsulation and orchestration
•    Selection and preparation of test data sets
•    Iteration management: definition, execution, evaluation
•    Definition and evaluation of functional/non-functional requirements
•    Development of technical conception derived from requirements
•    Creation of data pipelines for structured and unstructured data (ETL)
•    Data acquisition from web-based sources and third-party APIs
•    Conception and creation of data models
•    Data exploration and analysis
•    Data preparation and feature engineering
•    Creation, evaluation and integration of ML models
•    Creation of frontends for different stakeholders
•    Process automation and CI/CD
•    Rapid prototyping
•    Operation and maintenance, data quality assurance, code quality assurance

Techstack: SQL, python, pandas, sklearn, prophet, sktime, jupyter, atom, MS Visual Studio, beautifulsoup, selenium, bert, spacy, folium, rasterio, gdal, matplotlib, dash, pillow, geopandas, Azure Databricks, Azure HDInsight, Azure Blob Storage, Azure EH4Kafka, Azure Virtual Machines, Azure API Apps, Azure Functions, Azure Database for PostgreSQL, Azure Machine Learning, Azure logic Apps, Power BI, Amazon Redshift, Amazon EMR, Amazon S3, Amazon EC2, Amazon API Gateway, Amazon Lambda, Amazon Sagemaker
04/2011 - 10/2017
Data Scientist | Data Engineer | Project Manager | Team Leader | Architect
Company law enforcement, internal investigations, compliance (Internet and Information Technology, 10-50 employees)
Analysis of structured and unstructured data with modern approaches from the realm of Big Data and AI

•    Data cleansing / harmonization / integration / provisioning (ETL)
•    Analysis of data and creation of models to analyze data correlations
•    Presentation of data correlations and other results
•    Definition and evaluation of functional / non-functional requirements
•    Development of technical conception derived from the requirements
•    Creation of data pipelines for structured and unstructured data
•    Data acquisition from web-based sources and third-party APIs
•    Design and creation of data models
•    Data exploration and analysis
•    Data preparation and feature engineering
•    Creation, evaluation and integration of ML models
•    Design and development of an analysis framework
•    Management and project management activities

Techstack: SQL, PL/SQL, python, pandas, sklearn, jupyter, atom, spacy, folium, rasterio, gdal, matplotlib, dash, pillow, geopandas, PyTorch, Tensorflow, Oracle RDBMS, MongoDB, Neo4j, PostgreSQL, word2vec, HDFS, Hadoop ecosystem, Apache Spark, Hive
10/2010 - 04/2011
Project | Team leader Business Intelligence
Major International Bank (Banks and financial services, >10.000 employees)
Initiation and support of three projects in the environment of the company's future strategic DWH platform. The focus was on the conversion of the DWH core with special regards on IT security and data protection aspects as well as the support of the conversion of the development process from a waterfall to an iterative model.

•    Preparation Decision Making Management
•    Interface to the customer
•    Processing of status messages
•    Budget, time and quality responsibility
•    Monitoring of the budgeting processes
•    Technical leadership of the team
•    Preparation of project planning
•    Setting up resource planning
•    Preparation of the budget planning
•    Implementation of cost estimates
•    Reporting system
•    Analysis of requests/requirements

Techstack: SQL, PL/SQL, Oracle RDBMS, Informatica 
02/2003 - 10/2010
Different Roles Data Warehouse / Business Intelligence Platform
Major Telecommunications Company (Internet and Information Technology, >10.000 employees)
Overall architect

•    Definition of the overall architecture of the DWH within the Enterprise Warehouse
•    Advice to customers and other IT lines
•    Definition and enforcement of architectural definitions
•    Ensuring the correct distribution of the functional blocks within the EDWH
•    Ensuring compliance with corporate guidelines and legal requirements, in particular data protection regulations

Analyst/designer

•    Analysis of the technical requirements of the department
•    Analysis of data and processes in the source systems
•    Design of technical interface agreements
•    Preparation of technical interface agreements
•    Creation of logical data models
•    Design of the data flow within the DWH (ETL)
•    Design of the access layer (facts, dimensions)
•    Preparation of analyses and mathematical models

DWH Developer

•    Derivation of technical specifications on the basis of the requirements
•    Implementation of the specified modules (ETL)
•    ETL: Creation of data models (logical/physical)

Techstack: Oracle RDBMS, SQL, PL/SQL, Informatica
01/2000 - 01/2003
Data Engineer | Data Scientist | Team lead
Major Internet Service Provider (Internet and Information Technology, >10.000 employees)
Development of an ETL solution with operational elements and a data warehouse with the aim of gradually improving processes and implementing standard reporting. Connection to existing data warehouse structures. Development of a process-related datamart to provide a consolidated view of technically mapped business processes. Preparation of various analyses and reports.

•    Design ETL / DataMart / Reporting
•    Implementation ETL / DataMart / Reporting
•    Testing
•    Deployment

Techstack: Oracle RDBMS, SQL, PL/SQL

Local Availability

Open to travel worldwide
Remote preferred, any location possible
Profileimage by Anonymous profile, Data Scientist, Data Engineer, Business Intelligence, Data Warehousing, Big Data Data Scientist, Data Engineer, Business Intelligence, Data Warehousing, Big Data
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