Anita Okoh
AI Product Engineer at SAP
Berlin, Germany
Summary
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Rockstar🎓
Top SchoolAnita Okoh is an AI Innovation Engineer based in Berlin with seven years of experience building practical ML and data solutions across product and enterprise contexts. She has driven identity-resolution and graph analytics projects at Delivery Hero, automated ETL and schema generation with LLM agents at nuvo, and now focuses on AI innovation at SAP. Comfortable spanning engineering, data science, and technical writing, she contributes to prominent open-source frameworks like Superduper by improving developer-facing documentation and onboarding. Anita combines hands-on deployment experience (BERT embeddings, Node/TypeScript and Python stacks) with a knack for translating complex workflows into usable systems and clear docs. She also writes widely on data science topics and has led multidisciplinary teams in applied ML for social impact through Omdena. Her background in economics and formal training in generative AI and MLOps gives her a pragmatic lens for turning experiments into production-ready solutions.
7 years of coding experience
8 years of employment as a software developer
Prompt Engineering, Prompt Engineering at CourseraNanodegree Generative AI, Nanodegree Generative AI at UdacityCI/CD for Machine Learning, CI/CD for Machine Learning at DataCampBachelor’s Degree Economics, Bachelor’s Degree Economics at University of LagosDiploma Data Science, Diploma Data Science at SPICED Academy
English, German
Stackoverflow
1reputation
0reached
0answers
0questions
Github Skills (6)
documentation10
ai4
mlops3
python3
databases3
database3
Programming languages (2)
Github contributions (5)
superduper-io/superduper
Nov 2023 - Apr 2024
Superduper: End-to-end framework for building custom AI applications and agents.
Role in this project:
Technical Writer
Technical WriterContributions:4 reviews, 6 PRs, 4 pushes in 5 months
Contributions summary:Anita primarily contributed to the project by modifying documentation files. Their work involved updating sidebar configurations to include new data integrations and use case examples. Additionally, they updated links within example notebooks and adjusted use case names, all aimed at improving the usability and clarity of the documentation. The contributions focused on enhancing the user's understanding of the SuperduperDB framework through accurate and well-organized documentation.
aimlopstorchtransformersmongodb
anitaokoh/Streamlit_Python_Viz_App
Jan 2020 - Dec 2020
Check out visualizations using just python libraries
Contributions:92 commits, 74 pushes in 11 months
pythonvisualizations
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