Sebastian Hintergrundbild
Sebastian

Sebastian

DevOps, ML Engineer, Data Scientist, AWS Expert

Hamburg

Data Science
DevOps
Generative AI

Get AI productive to solve problems, not create them

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Reputation

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Kontakte

Kontakte

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Über Junico
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Über mich

- Background in process engineering, resulting in strong scientific, analytical, and problem-solving skills - Over 5 years of experience as a Data Scientist and AWS Cloud Engineer - Trained and prototyped over 20 Machine Learning models for various AI use cases and clients - Led deployment of two ML models at scale on the AWS Cloud, earning the WirtschaftsWoche Best of Consulting Technology Award 2020 - Experience in diverse areas: Data Security in ML, AI-driven Drug Design, Named-Entity Recognition, Predictive Maintenance, GenAI and more - Led the development of two AI Platforms for enterprise clients, and build my own MLOps template repository, streamlining ML deployments and operations

Skills

Expert:in

Data Science
DevOps
Generative AI
Amazon Web Services
Machine Learning
AI Development
Cloud Computing
Python
AI Image Generation
AI Consulting
Data Analysis
Data Visualisation
Free and Open-Source Software
Prototyping
Infrastructure Strategy
Software Design
Infrastructure Design
Infrastructure Deployment
Microservices
Backend Development
Automatisierungstechnik
Automationssysteme
Data Protection Management
UX Design
AI Application

Fortgeschritten

Data Engineering
Applications Development
Softwareentwicklung
Data Strategy
Data Governance
Business Innovation
Software Testing
Product Development
AI Content Creation
Cyber Risk Management
Risk Compliance and Governance
Stakeholder Management
Operatives Projektmanagement
Agile Software Development
AI Ethics and Governance

Junior:in

Business Process Reengineering
Disaster Recovery
OAuth

Portfolio

Training and Deploying of NLP Classification Model for Booking Emails on AWS, Handling ~3,000 Emails per Day

Training and Deploying of NLP Classification Model for Booking Emails on AWS, Handling ~3,000 Emails per Day

AI Team Strategy Assessment and Guidance on how to Scale-Up AI Operations via In-House AI Platform

AI Team Strategy Assessment and Guidance on how to Scale-Up AI Operations via In-House AI Platform

Protein Atlas Kaggle Challenge

Protein Atlas Kaggle Challenge

Projekte

  • AI Team Strategy Assessment and Guidance on how to Scale-Up AI Operations via In-House AI Platform

    Hapag-Lloyd · Transport & Logistik

    2022

    Role: Senior Data Scientist and Project Manager

    Technologies used: AWS Cloud Services, MS Office, Miro

    • Collection of user stories and IoT use cases from various customer departments
    • Collecting capabilities and technical requirements for IoT platform as evaluation grid
    • Interviews with stakeholders and dev teams to identify the biggest challenges of current and planned IoT projects
    • Evaluation of make (on-prem) vs buy (full vendor solution) vs make&buy (cloud platform as a service)
    • Technology stack discussion and tooling recommendations
    • Conceptual creation of AWS architecture diagrams in collaboration with Cloud Expert- Prioritization and creation of development roadmap
    • Presentation to stakeholders and management
  • Vendor Evaluation and Cloud Architecture Design for Scalable IoT Data Platform to Track 2 Mio. Shipping Containers

    Hapag-Lloyd · Transport & Logistik

    2022

    Role: Senior Data Scientist and Project Manager

    Technologies used: AWS Cloud Services, MS Office, Miro

    • Collection of user stories and IoT use cases from various customer departments
    • Collecting capabilities and technical requirements for IoT platform as evaluation grid
    • Interviews with HL stakeholders and dev teams to identify the biggest challenges of current and planned IoT projects
    • Evaluation of make (on-prem) vs buy (full vendor solution) vs make&buy (cloud platform as a service)
    • Technology stack discussion and tooling recommendations
    • Conceptual creation of AWS architecture diagrams in collaboration with Cloud Expert
    • Prioritization and creation of development roadmap
    • Presentation to stakeholders and management 
  • Proof of Concept for Detection of Damages on Train Wheels via Pressure Sensors on the Track to Enable Predictive Maintenance

    DB · Transport & Logistik

    2021 — 2022

     Role: Senior Data Scientist

    Technologies used: AWS Cloud Services, Python, Pandas, Scikit-learn, PyTorch, VS-Code, Git

    • Interviews with the customer's experts and engineers
    • Data preparation and merging of time series data from measurement systems and maintenance data from SAP
    • Descriptive analysis and cleaning of data
    • Feature engineering and development of a baseline model (random forest)
    • Successful training of an autoencoder model to reduce dimensional complexity by 64%
    • Development of a "Rolling-RANSAC" model to predict risk of wheel damage
    • Documentation

     

Berufserfahrungen

  • Senior Data Scientist, ML Engineer, CEO and Founder · Vollzeit

    q·ops · Internet und Informationstechnologie

    2022 — 2024

    • Writing business plan, user stories and collecting AI use cases from various customers
    • Gathering capabilities and technical requirements for AI platform as evaluation grid
    • Designing and prototyping various cloud architectures for model serving and deployment
    • Implementation of scalable and serverless infrastructure as code
    • Creation of repository template with custom Python package and automations
    • Implementation of end-to-end MLOps stack including CI/CD pipelines for models and code, staging environments etc.
    • Recording course to teach and onboard users who are new to AWS and MLOps

    Technologies used: Python, AWS Cloud Services, Just, GitHub, DVC, Metaflow, Webflow etc.

     

  • Senior Data Scientist · Vollzeit

    Ginkgo Analytics · Beratung und Consulting

    2021 — 2022

    • Led stakeholder interviews, vendor evaluation and cloud architecture design for scalable IoT data platform to track over 2 Mio. shipping containers at Hapag-Lloyd
    • Assessment of AI team strategy and tech stack, providing actionable plan on how to accelerate and scale-up AI operations by improving in-house AI platform
    • In depth data analysis and implementation of ML model prototype for detecting damages on train wheels via pressure sensors on the track to facilitate predictive maintenance
    • Led and participated as Data Scientist in the planning and implementation of an AI Platform on AWS to streamline ML deployments and operation for large networking provider
    • Build Dash prototype for self-learning NLP web app for information extraction from contracts for large networking provider
    • Planning the design and implementation of a data-driven and AI-assisted drug discovery application for chemists in large pharma company
  • Data Scientist · Vollzeit

    Ginkgo Analytics · Beratung und Consulting

    2019 — 2021

    • Evaluating the potential of reverse engineering training data by performing different attacks on deployed drug design models, to protect the integrity of pharmacological compounds
    • Prototyping of 10 and deployment of 2 NLP models in cloud environments, automating high-volume email handling tasks for Hapag-Lloyd

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