Data Scientist

he candidate should at minimum show proficiency in:

• Strong Python and intermediate SQL skills
• Experience building, deploying, and evaluating ML/NLP/GenAI systems.
• Experience with ML system design
• Very strong (including written) communication skills and ability to break down and articulate complex tasks into implementation strategies
• Software engineering best practices, including testing, OOP, etc.
• Knowledge of cloud systems, especially azure preferred.
• A more traditional ML perspective, some knowledge and understanding of mathematical optimizers, how to select the best ones for purpose and set parameters

Must Have:

• Experience working closely with other data scientists, data engineers’ software engineers, data managers and business partners.
• Can build scalable, re-usable, impactful data science products, usually containing statistical or machine learning algorithms, in collaboration with data engineers and software engineers.
• Can carry out data analyses to yield actionable business insights.
• Hands-on experience (typically 5+ years) designing, planning, prototyping, productionizing, maintaining and documenting reliable and scalable data science products in complex environments.
• Applied knowledge of data science tools and approaches across all data lifecycle stages.
• Thorough understanding of underlying mathematical foundations of statistics and machine learning.
• Development experience in one or more object-oriented programming languages (e.g. Python, Go, Java, C++)
• Advanced SQL knowledge.
• Knowledge of experimental design and analysis.
• Customer-centric and pragmatic mindset. Focus on value delivery and swift execution, while maintaining attention to detail.