Karyna Naminas is an accomplished and results-oriented Data Scientist based in Berlin, Germany, with approximately 7 years of dedicated experience in leveraging advanced analytics, machine learning, and artificial intelligence to solve complex business problems and drive innovation. Her expertise encompasses the full data science lifecycle, from data acquisition, cleaning, and exploratory data analysis to model development, validation, deployment, and MLOps. Karyna is highly proficient in Python, R, SQL, and a wide array of machine learning libraries (e.g., Scikit-learn, TensorFlow, PyTorch) and big data technologies (e.g., Spark, Hadoop). She has a strong track record of developing predictive models, natural language processing solutions, and recommender systems across various industries, consistently translating data-driven insights into actionable strategies and tangible business value. Karyna is passionate about ethical AI and continuously explores cutting-edge techniques to stay at the forefront of the field. She is an effective communicator, capable of conveying complex technical findings to both technical and non-technical stakeholders.
Karyna Naminas's work history includes a series of influential roles in various companies. Here is a detailed list of his professional journey:
Spearheaded the development and deployment of a machine learning-based customer churn prediction model that improved customer retention by 18% within the first year of implementation by identifying at-risk customers for targeted interventions.
Designed and implemented an NLP engine to analyze customer feedback from various sources (surveys, social media, reviews), providing actionable insights that led to a 25% improvement in product iteration speed and enhanced customer satisfaction scores.
Developed a predictive analytics solution for supply chain optimization, resulting in a 12% reduction in logistical costs and a 15% improvement in delivery timeliness by forecasting demand and optimizing inventory levels.
Co-authored and published a paper in a reputable AI conference proceedings on novel techniques for enhancing the interpretability of complex machine learning models, contributing to the growing field of Explainable AI.
Actively mentored junior data scientists and aspiring female technologists through a 'Women in Tech' initiative, contributing to diversity and inclusion within the technology sector.
UCU Business School (LvBS) - Year 2024
Borys Grinchenko Kyiv University - Year 2017
St George's School, Ascot - Year 2014
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