Over 3 years of experience working with PL/SQL and RDBMS, especially SQL Server.
Solid understanding of ETL patterns and processes.
Expertise in processing and analyzing large datasets to identify patterns, uncover opportunities, and contribute to actionable solutions.
Over 3 years of experience with machine learning frameworks such as Keras or PyTorch and libraries like scikit-learn.
Over 3 years of experience in Python programming, including proficiency with the Pandas library.
Strong knowledge of machine learning concepts and techniques, including supervised and unsupervised learning, time-series forecasting, and recommender systems.
Proficient in mathematics, probability, statistics, and algorithms.
Familiarity with sequence models in deep learning, such as LSTMs and Transformers.
Skilled in performing statistical analysis and fine-tuning models based on test results.
In-depth understanding and hands-on experience with ML Ops and end-to-end deployment of AI/ML solutions.
Proficiency in building machine learning and data processing pipelines.
Strong analytical skills, particularly in working with unstructured datasets.
Expertise in model implementation, data structures, data manipulation, distributed processing, application development, and automation.
Experience with Big Data ecosystems and distributed storage (preferred).
Commitment to developing and maintaining high-quality code aligned with best practices.