Martynas Lukosevicius

• Establishing GCP-based data stack, including ETL pipelines, data warehouse, and reverse ETL. Resulted in enhanced data management and analysis, reducing data processing time by 60%. • Conducting A/B testing, MMM, time series analysis and forecasting, informing data-driven decisions with a contribution to a 52% improvement in revenue. • Integrating Terraform into the data warehousing system, automating cloud resource provisioning and management resulting in a 4x reduction in client onboarding time.

• Conducted research on the application of a deep reinforcement learning algorithm for autonomous ship steering, ensuring adherence to maritime laws, collision avoidance, and ability to follow predefined paths. • Designed and implemented the process simulation model for the research, providing a realistic testing and training environment for the Proximal Policy Optimisation (PPO) model.

- Demonstrated exceptional communication and problem-solving abilities as a teaching assistant for a computational statistics course - Enhanced students’ learning experience by providing personalized assistance with assignments and answering relevant questions - Demonstrated exceptional communication and problem-solving abilities as a teaching assistant for a computational statistics course

• Enhanced enterprise software using data science expertise such as metainformation, resulting in an 8x faster processing speed and 13.4% F1-score boost. Contributed to significant performance achievements. • Proficient in Python and data science libraries (asyncio, requests, BeautifulSoup, Scikit-learn, and PyCaret) to develop advanced data science solutions, reducing development time by 20% through efficient coding.

• Managed major projects by using Agile methodology and tools such as Git, Jira, Java, and SQL, ensuring project efficiency and resulting in on-time project delivery. • Identified and resolved hardware and software issues such as software bugs, ensuring seamless operation of the automated storage and retrieval system, minimising disruptions.

• Successfully led the commissioning of an automated storage and retrieval system for a food retail warehouse. Contributed to a 3x reduction in order fulfilment time. • Mentored and trained 5+ junior controls engineers in the preparation to manage a new automated warehouse. Resulted in an overall improvement of maintenance practices. • Developed software debugging tools such as C# for error detection, streamlining work processes and resulting in a 20% higher work efficiency.

spaCy · PySpark · R · Python · Machine Learning · AI · Statistics · Data Mining · SQL · Relational Databases · TensorFlow · Keras · Machine Learning Algorithms · Spark · Git · NumPy · Scikit-Learn