I am a data expert in the process of becoming a data scientist.A data person all my life, I have recently delved into data science and machine learning, after 20 years working as senior data analyst and linguistic expert in the speech technology industry.My data science background is self-taught. My project 'socioeconomic classifier', available on my github, covers various aspects of ML-based classification, including: classifier construction, optimization, comparison, custom loss function and metric, and of course all aspects of data handling. I encourage you to visit my github project page and review the presentation and the Python code. I believe it demonstrates my self-learning abilities, as well as clean and elegant coding. Use the following url to access the project page:https://github.com/RoyBeckerKristal/socioeconomic_classifierMy recent passion for data science stems directly for my lifelong passion for data, well manifested in my academic background, my career so far and personal interest as well.My academic background (BA, MA, PhD) is in linguistics, focusing on what is perhaps the most empirical and numerical linguistic field: phonetics. My UCLA PhD research and dissertation were a major data analysis project, where I collected, processed and applied rigorous statistical meta-analyses over acoustic vowel data from 230 different languages. My dissertation established empirical support for a particular theory on speech sound organization. In addition, my research involved developing computer simulations for testing predictions of vowel organization models.During my 19 years as linguistic data expert in the speech industry I have been the data focal point for engineers and developers, and was in charge of the entire phonetic and linguistic data cycle for ML-based solutions, as well as devising and developing complementary heuristic logics and user/product-oriented features.My ideal job would be on the border and interface between data science and analysis. I want to use my deep understanding and intuition for the data of the problem, as part of my role and contribution to tailoring the optimal ML-based solution for the problem.