Yerbolat Assylbek - Product Data Analyst

Yerbolat Assylbek

Product Data Analyst

Astana, Astana, Kazakhstan

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Summary

👤

Senior

🎓

Top School

Yerbolat Assylbek is a Product Data Analyst with 10 years of experience turning complex financial and operational data into clear, actionable insights for startups and large organizations. He specializes in SQL-driven analytics and scalable data workflows, having built revenue and churn reporting, automated pipelines, and QuickSight/Power BI dashboards used by Finance, Product, Sales, and CEOs. His background spans institutional research and product management, giving him a rare blend of rigorous statistical methods (STATA, SPSS) and hands-on product delivery that has directly supported multi-million dollar revenue KPIs. Yerbolat also contributes to open-source speech processing tooling (ESPnet), reflecting active technical engagement beyond pure analytics into ASR pipeline work. Based in Astana, he is passionate about automating reporting, improving data quality, and enabling self-service analytics across organizations.

10 years of coding experience

7 years of employment as a software developer

Bachelor's degree, Telecommunications, 3.7, Bachelor's degree, Telecommunications, 3.7 at Penn State University

Master’s Degree, Economics, 3.42, Master’s Degree, Economics, 3.42 at Nazarbayev University

Study abroad, Economics, Study abroad, Economics at Monash University

Github Skills (8)

sh10

script10

speech-recognition10

shell10

scripting10

python9

pytorch9

machine-translation5

Programming languages (3)

ShellPythonCuda

Github contributions (5)

espnet/espnet

Mar 2019 - May 2023

End-to-End Speech Processing Toolkit

Role in this project:

Back-end Developer

Contributions:1 PR, 3 comments, 2 issues in 4 years 2 months

Contributions summary:Yerbolat's contributions primarily focus on updating configuration and data preparation scripts within the `egs2/ksc/asr1` directory. These updates involve modifying `prepare_data.sh` and `run.sh` scripts, likely related to data processing and model training/evaluation procedures for an Automatic Speech Recognition (ASR) task. The changes suggest involvement in the configuration and execution of the ASR pipeline within the ESPnet framework, affecting data input, training parameters, and testing procedures. The work demonstrates practical engagement with the core processes of speech recognition.

speech-recognitionspeech-separationchainerspoken-language-understandingspeech-processing

khassanoff/ASR_text_normalization

Jun 2016 - Jun 2019

Contributions:10 commits, 8 pushes, 1 branch in 3 years 1 month

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