Thomas Mick

data scientist / data engineer / bi dev / dwh

Peut se déplacer à Paris, Nantes, Lyon

  • 48.8546
  • 2.3477
Proposer un projet La mission ne démarrera que si vous acceptez le devis de Thomas.
Proposer un projet La mission ne démarrera que si vous acceptez le devis de Thomas.

Localisation et déplacement

Paris, France
Peut travailler dans vos locaux à
  • Paris et 50km autour
  • Nantes et 50km autour
  • Lyon et 100km autour


Durée de mission
  • ≤ 1 semaine
  • ≤ 1 mois
  • entre 1 et 3 mois
  • entre 3 et 6 mois
  • ≥ 6 mois
Secteur d'activité
Préfèrerait éviter:
  • Défense & armée
  • Restauration
  • Commerce de détail
Taille d'entreprise
  • 2 - 10 personnes
  • 11 - 49 personnes
  • 50 - 249 personnes
  • 250 - 999 personnes
  • 1000 - 4999 personnes
+1 autres




Compétences (25)

  • Databases
  • Débutant Intermédiaire Confirmé
  • Débutant Intermédiaire Confirmé
  • Débutant Intermédiaire Confirmé
  • Débutant Intermédiaire Confirmé

Thomas en quelques mots

Probably the most interesting development in the general field of Data Science is that we left behind the era where extracting data and the information contained in it is perceived as an privilege for big companies.

Nowadays all the tools we need can be obtained from public available Open Source Projects and data, of course, can still be found everywhere.

If you need someone that can give you a helping hand with extracting knowledge for your needs you might want to consider contacting me so I can explain to you how you can benefit from my 20+ years experience in that field.

No matter where you are right now and where you want to go I am sure I can support you. Although I am very proficient with every aspect of Data Engineering and Data Science You will remain my center of gravity not the data pipeline I will create for you.

As a Mathematician I wrote my thesis about time series forecast with neural networks before working in the field of Business Intelligence in big companies for eleven years. After that I enhanced my working experience by adding Big Data frameworks and methodologies to my portfolio. For the last three years I work in the exciting Startup Ecosystem, always eager to apply my skills I learned in an industrial environment in large teams to create added value.

Besides my main tasks I work as a professor for Big Data, Machine Learning and future technologies in an internationally top rated university for three years now.

Please feel free to contact me if you have further questions.


Portfolio uniquement accessible aux membres


Startup digital platform for sustainable development

Voyage & tourisme

Data Scientist / Data Engineer / CTO and CoFounder

Paris, France

octobre 2019 - Aujourd'hui

We create 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
  • 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

University in Germany

Education & e-learning

Professor (part time lecturing)

Frankfurt am Main, Germany

octobre 2018 - Aujourd'hui

Currently I am lecturing once per semester in the following areas:

  • Big Data
  • Databases
  • AI / machine learning
  • Future technologies and society

Startup AI Service Platform

High tech

Data Scientist, Data Engineer, Architect

Frankfurt am Main, Germany

octobre 2017 - septembre 2019

Development of a platform for the use of micro-service based machine learning models in operative IT environments and the business processes integrated in them.

  • High-level design of the overall system
  • Conception general 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, implementation, evaluation

Data Science Consulting Company for law enforcement, internal investigations, compliance

Conseil & audit

Data Scientist, Data Engineer, Project Manager, Team Leader, Architect

Frankfurt am Main, Germany

avril 2012 - octobre 2017

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