Data Scientist|ML Developer

3/2022 – 7/2023

Integrated (tested, benchmarked, adjusted/twitched) Machine Learning models into the final product. Refactored and documented legacy code to adhere to clean principles and performed code partitioning. Developed logging strategy in collaboration with team’s Tech Lead and Product Manager. Implemented an in-house log analytics pipeline, harnessing AWS services and Python packages such as AWS Data Wrangler, Boto3, Matplotlib, Pandas, and Numpy for efficient data processing and visualisation. Organised knowledge sharing sessions for colleagues, prepared a series of presentations.

Amazon Web Services (AWS), Git, Pandas DataFrame, Python, Testing (IT)

3/2022 – 7/2023

Proposed and presented to stakeholders the design of speech-to-text pipeline. Implemented proposed solution. Improved efficiency by fine-tuning automatic speech translation and natural language processing models, leveraging scikit-learn, TensorFlow, and Kaldi. As a result pipeline’s accuracy was significantly increased. Optimised Coqui TTS text-to-speech models. Worked with user feedback converting it to actionable tasks improving User Experience.

Agile Entwicklung, Amazon Web Services (AWS), Git, Maschinelles Lernen, Natural Language Processing (NLP), Pandas DataFrame, Python, TensorFlow

9/2019 – 12/2021

Led practical and theoretical seminars, helping students to conduct their experiments in R.
Participated in developing and launching the first online course for 'Statistics and Data Analysis' via GitHub during the COVID-19 pandemic.
Led a project in Closed-loop Control Systems with Machine Learning, sharing expertise in merging control systems and machine learning techniques.

Git, Lineare Regression, Naive Bayes, Python, R (Programmiersprache), Statistik (allg.), Statistische Versuchsplanung (SVP)