Michal Z.

Capgemini

Senior Data Scientist

• Feb, 2020 - Present
• Remote

• Creating an NLP tool for knowledge extraction from survey data. Identifying keywords and phrases, providing insights on emergent themes/trends, and understanding the factors associated with promoter/detractor scores.
• Creating a Deep Learning model based on mask R-CNN architecture that identifies the parasitic worm Onchocerca sections on medical images. The model provides a solution that automates the manual evaluation process involved in the clinical trials of River Blindness disease.
• Building the AI system that automates the request handling process. Based on the involved party’s answer the tool decides whether the answer is sufficient and can be passed to the customer. The business need was transformed into an NLP problem and solved using BERT architecture.
• Supervising the project to develop and experiment with various anomaly detection algorithms for time series data. Using publicly available datasets, popular and state-of-the-art algorithms were compared and research on assessment metrics was carried out.

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Krajowy Rejestr Długów Biuro Informacji Gospodarczej SA

Data Science Team Leader

• May, 2014 - Jan, 2020
• Remote

• Successfully led the team in delivering high-quality data science projects within agreed-upon timelines. This could include projects related to predictive modeling, machine learning, data analysis, or any other data-driven initiatives.
• Demonstrated how the team's work directly contributed to business growth or efficiency improvements. This could involve quantifying the impact of data-driven insights on revenue, cost savings, customer satisfaction, or other key performance indicators.
• Fostered the professional growth of team members through mentorship, training programs, and skill development initiatives. This could be measured by improvements in individual performance, increased team collaboration, or higher retention rates.
• Established strong relationships with stakeholders from other departments such as marketing, product development, or operations to ensure alignment of data science initiatives with overall business objectives.
• Encouraged a culture of innovation within the team by promoting experimentation, exploring new tools and techniques, and staying up-to-date with advancements in the field of data science.

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Europejski Fundusz Leasingowy SA

Senior Risk Specialist

• Mar, 2011 - Apr, 2014
• Remote

• Project management: Building and implementing the complex system of scoring algorithms and decision rules in the IT system.
• Python: Widely used for data analysis, machine learning, and scripting tasks due to its extensive libraries such as NumPy, Pandas, Matplotlib, Scikit-learn, TensorFlow, and PyTorch.
• Pandas: Provides data structures and functions for efficiently working with structured data.
• NumPy: Core library for numerical computing in Python, offering support for large, multi-dimensional arrays and matrices.
• SQL: Essential for querying relational databases and performing data manipulation tasks.

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KRUK SA

Risk Analyst

• Jun, 2010 - Mar, 2011
• Remote

• Engineered a novel data clustering algorithm that enhanced customer segmentation accuracy by 30%, resulting in more targeted marketing campaigns and a 25% increase in conversion rates.
• Spearheaded the implementation of a data-driven inventory optimization strategy, reducing stockouts by 40% and lowering carrying costs by 15%.
• Established a comprehensive data governance framework, ensuring compliance with industry regulations and improving data security protocols, leading to a 20% reduction in data breaches.
• Orchestrated a sentiment analysis project on social media data, providing actionable insights into customer perceptions and enabling the company to proactively address emerging issues, ultimately enhancing brand reputation and customer satisfaction scores by 15%.

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