Data Scientist-Machiner Learning (ML)

• A Bachelor’s degree in Data Science or a quantitative field, such as Finance,
Computer Science, Economics, Mathematics or a similar technical discipline
and 5+ years’ experience
in applying analytics, data engineering or data science; or
• Master's Degree or PhD in Data Science or a quantitative field, such as
Finance, Computer
Science, Economics, Mathematics or a similar technical discipline and 2+
years’ experience
in applying analytics, data engineering or data science.
• Proficiency in working with SQL, Python across complex real world datasets
• Proficiency in using modern data visualization tools, such as Tableau,
PowerBI or similar.
• Experience deploying ML models using machine learning as a service
platforms such as
Amazon SageMaker, Google Cloud AI, and Microsoft Azur.
• Excellent written and verbal communication skills.
• Aptitude for critical thinking as it relates to complex problems and challenge
assumptions
in order to implement creative solutions.
• Experience applying data science consumer finance, fintech and other
Financial
Industry domains.
• Familiarity with related disciplines such as consumer finance, project
management,
user experience design, software development and digital marketing
• Experience in establishing data technology foundations for agile business
intelligence,
data lakes and data workbenches, and applied machine learning/AI.
• Experience with large-scale data analysis technologies (e.g. Relational and
NoSQL