Description

You will own the end-to-end data lifecycle for risk and strategy decisions, leveraging Python and SQL to drive business outcomes.

Responsibilities

• Evaluate and implement business strategies using large, complex internal and external datasets.
• Compile and retrieve data via SQL and Access to predict and measure key business successes.
• Document data requirements, then perform collection, cleaning, and exploratory analysis using statistical models.
• Apply machine learning algorithms and data visualization techniques to present insights to stakeholders.
• Assess risk in business decisions, ensuring compliance with laws, regulations, and ethical standards.

Required Skills

• 8+ years of experience in quantitative analysis, preferably within financial services or credit card industries.
• Proficiency in Python for data science, including data manipulation and statistical modeling.
• Strong SQL skills for data retrieving, complex queries, and database management.
• Experience with Machine Learning and statistical modeling to solve complex business problems.
• Ability to conduct exploratory data analysis and translate findings into actionable business recommendations.
• Proficiency in MS Excel and data visualization tools to present findings effectively.
• Strong problem-solving, organizational, and communication skills to work in a matrix environment.

Preferred Skills

• Master's degree in a quantitative field.
• Knowledge of marketing, risk, digital, and AML domains.
• Proficiency in Access database management.

Key Skills

Education

Any Graduate