Job description
Requirements
Experience using statistical computer languages (R, Python, SLQ, etc.) to manipulate data and draw insights from large data sets.
Ability to work with both structured and unstructured data and come up with solutions and strategies to business challenges.
Ability to process data and present it through visuals and communicate to both a technical and non-technical audience.
Knowledge of advanced statistical techniques and concepts.
Experience working with and creating data architectures.
Knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and their real-world advantages/drawbacks.
Ability to develop custom data models and algorithms to apply data sets.
Ability to develop processes and tools to monitor and analyze model performance and data accuracy.
Experience and Qualifications
Proven experience as a Data Scientist or Data Analyst.
Experience in Data Science for Credit Decisioning will be a major advantage.
Experience in data mining.
Understanding of machine-learning and operations research.
Experience using business intelligence tools (e.g. Tableau) and data frameworks (e.g. Hadoop).
Knowledge of R, SQL and Python; familiarity with Scala, Java or C++ is an asset.
Analytical mind and business acumen.
Strong math skills (e.g. statistics, algebra).
Problem-solving aptitude.
Excellent communication and presentation skills.
Advanced Degree or BSc/BA in Computer Science, Engineering, Mathematics or relevant field; graduate degree in Data Science or other quantitative field is preferred.
A drive to learn and master new technologies and techniques.
