Associate Data Scientist (Hybrid)

Key Skills

Java Programming, Finance, Risk Analytics, Python Programming, SQL, AWS, Machine learning techniques, Data Modeling, Amazon Athena, R Programming, Amazon Elastic Compute Cloud-EC2, Amazon Simple Storage Service (S3), Data Wrangling, Terabyte scale datasets, Data Analysis

Job Description

We are looking for a data scientist to join our Predictive Analytics team. Our team is directly involved in the development of a wide range of analytical solutions, including credit risk metrics, supply risk, interest rate risk, liquidity risk, and climate risk. Our data scientists contribute to diverse projects in every phase, including data analysis, methodology design, model development and enhancement, documentation writing, results delivery, and interpretation. We are looking for collaborative, highly motivated individuals with strong quantitative and communication skills, willing to learn and develop in a very dynamic and multicultural environment.

• Work in a cross-functional environment. Conduct ad-hoc data analysis and provide technical assistance for strategy and other client-facing teams.
• Explore large structured and unstructured datasets for new product development.
• Provide analytical tools supporting product development decisions.
• Model risk, using state-of-the-art statistical and econometric techniques, including forecasting and simulation exercises
• Collaborate with financial researchers and data analysts on research projects
• Partner with engineering teams to deploy completed research through various technology channels
• Present research findings to technical and non-technical audiences internally and externally.

Qualifications

Required:

• Strong academic background – MS degree in in Financial Engineering, Data Science, Statistics, Economics, Econometrics, Mathematics, Physics, Finance, or another relevant field.
• Data wrangling experience.
• AWS experience: EC2, Athena, S3
• Advanced programming skills in R, Python, SQL.
• Strong analytical, interpersonal, and organizational skills
• Excellent written and oral communication skills.
• Demonstrated ability to communicate technical content clearly and concisely to non-technical audiences.
• Must be an intrinsically motivated, responsible person who can work well with others, independently of daily supervision.

The successful candidate will also possess the following qualities:

• Adaptable
• Strong attention to detail
• Effective time manager

Preferred:

• Research experience in econometric modeling and/or machine learning.
• Industry experience in quantitative risk modeling and/or knowledge of banking regulations in the areas of risk measurement and monitoring, macroeconomic forecasting, and stress-testing.
• Experience in a client-facing position in financial services or consulting.
• Experience in or knowledge of credit underwriting, Basel regulation, portfolio management or credit & equity research
• Experience with business strategies such as risk-based pricing, limit-setting, limit management, and collection.