Sebastian

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

Open Source

Prototyping

Infrastructure Strategy

Software Design

Infrastructure Design

Infrastructure Deployment

Microservices

Backend Development

Automatisierungstechnik

Automationssysteme

DPM

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

RCG

Stakeholder Management

Operatives Projektmanagement

Agile Development

AI Ethics and Governance

Grundkenntnisse

BPR

Disaster Recovery

OAuth

Projekte

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

Hapag-Lloyd · Transport & Logistik · 1.000+ Mitarbeiter:innen

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 · 1.000+ Mitarbeiter:innen

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 · 1.000+ Mitarbeiter:innen

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

Alle Projekte ansehen

Berufserfahrungen

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

q·ops · Internet und Informationstechnologie · 1 Mitarbeiter:innen

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 · 25–50 Mitarbeiter:innen

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 · 10–25 Mitarbeiter:innen

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

Alle Berufserfahrungen ansehen

Get AI productive to solve problems, not create them

Über mich

Skills

Portfolio

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

Protein Atlas Kaggle Challenge

Projekte

Berufserfahrungen

So funktioniert Junico

Sebastian ist Freelancer:in bei Junico