Senior Data Scientist
We are seeking a highly skilled and experienced Senior Data Scientist to join our dynamic team. The ideal candidate will bring a deep understanding of statistical modeling, machine learning, and data engineering, and will apply these skills to solve complex business problems and drive strategic decision-making.
Required Qualifications:
• Bachelor’s degree in Computer Science or a Master’s degree (or higher) in Data Science, Information Systems, Computer Science, or a closely related field. A PhD is preferred.
• At least 7 years of hands-on experience in machine learning, deep learning, and predictive modeling in a commercial setting.
• Prior experience with ML is required.
• Proficiency in Python programming is required.
• Deep understanding of Natural Language Understanding (NLU), Computer Vision, Statistical Modeling, Data Visualization, and advanced Data Science methodologies.
• Skilled in extracting insights from text data, including handling non-language tokens.
• Capable of performing thorough error analysis of models and clearly communicating findings to technical and non-technical stakeholders.
• Able to apply image annotation concepts to text analysis tasks.
• Expertise in dimensionality reduction techniques (e.g., PCA) and able to articulate their impact.
• Strong understanding of model interpretability what contributes to model performance and how to optimize it.
• Experience with modern deployment and delivery technologies including Kubernetes, Containers, Docker, REST APIs, GraphQL, and Event Streams.
Preferred qualifications:
• Experience applying discrete mathematics, differential equations, deterministic and probabilistic models to real-world problems particularly within Finance, FinTech, or scoring systems.
• Experience in Software Development, Data Engineering, or Data Science programming is highly desirable.
• Expertise in interpreting and validating models through statistical methods, classical machine learning, deep learning architectures, and cutting-edge techniques like Transformer models and attention mechanisms.
• Strong capabilities in data modeling, querying, structuring, and designing data architectures.
• Familiarity with risk assessment frameworks and credit risk modeling.
• Experience within Finance or FinTech domains is a strong plus.
We are seeking a highly skilled and experienced Senior Data Scientist to join our dynamic team. The ideal candidate will bring a deep understanding of statistical modeling, machine learning, and data engineering, and will apply these skills to solve complex business problems and drive strategic decision-making.
Required Qualifications:
• Bachelor’s degree in Computer Science or a Master’s degree (or higher) in Data Science, Information Systems, Computer Science, or a closely related field. A PhD is preferred.
• At least 7 years of hands-on experience in machine learning, deep learning, and predictive modeling in a commercial setting.
• Prior experience with ML is required.
• Proficiency in Python programming is required.
• Deep understanding of Natural Language Understanding (NLU), Computer Vision, Statistical Modeling, Data Visualization, and advanced Data Science methodologies.
• Skilled in extracting insights from text data, including handling non-language tokens.
• Capable of performing thorough error analysis of models and clearly communicating findings to technical and non-technical stakeholders.
• Able to apply image annotation concepts to text analysis tasks.
• Expertise in dimensionality reduction techniques (e.g., PCA) and able to articulate their impact.
• Strong understanding of model interpretability what contributes to model performance and how to optimize it.
• Experience with modern deployment and delivery technologies including Kubernetes, Containers, Docker, REST APIs, GraphQL, and Event Streams.
Preferred qualifications:
• Experience applying discrete mathematics, differential equations, deterministic and probabilistic models to real-world problems particularly within Finance, FinTech, or scoring systems.
• Experience in Software Development, Data Engineering, or Data Science programming is highly desirable.
• Expertise in interpreting and validating models through statistical methods, classical machine learning, deep learning architectures, and cutting-edge techniques like Transformer models and attention mechanisms.
• Strong capabilities in data modeling, querying, structuring, and designing data architectures.
• Familiarity with risk assessment frameworks and credit risk modeling.
• Experience within Finance or FinTech domains is a strong plus.
