Benefits:

• Bonus

Education Requirements:

• Bachelor’s or Master’s degree in Statistics, Mathematics, Computer Science, or a related field is preferred

Experience Requirements:

• 4-7 years in data science, with a strong record of driving business impact

Other Requirements:

• Proficiency in Python, Power BI, SQL, and data manipulation tools; experience with cloud platforms (Snowflake, AWS SageMaker, Azure AI) and MS Power Apps.

• Skilled in a variety of machine learning techniques, including clustering, decision trees, neural networks, and natural language processing (NLP)

• Solid understanding of advanced statistical techniques and real-world application

• Strong written and verbal communication skills

Responsibilities:

• Collaborate with internal teams to identify and prioritize opportunities for leveraging data in product development, marketing strategies, and business processes.

• Extract and interpret data to create actionable insights that drive business growth and customer engagement.

• Evaluate the accuracy of new data sources and data collection methods.

• Develop and deploy custom algorithms and predictive models to optimize customer experience, boost revenue, and refine ad targeting.

• Establish and refine an A/B testing framework to evaluate model performance. Coordinate with cross-functional teams to implement models and track their outcomes in real-time. Design tools and processes to monitor data accuracy and model effectiveness

Benefits:

• Bonus

Education Requirements:

• Bachelor’s, Master’s, or Ph.D. in Computer Science, Statistics, Data Science, or STEM fields. Alternatively, a strong Finance or Business background paired with technical expertise

Experience Requirements:

• 5+ years working with complex data systems (Oracle, SQL)

• 5+ years in software/data engineering, especially within financial services

• 3–5 years in financial modeling or analytics roles

Other Requirements:

• Proficiency in Python, SAS, or R

• Hands-on experience with cloud platforms like AWS, Azure, or GCP

• Expertise in statistical modeling and machine learning techniques

• Analytical thinker with a knack for problem-solving

• Exceptional organizational and time management skills

• Strong communication skills to bridge technical and non-technical teams

• Background in full-stack development

• Knowledge of CI/CD pipelines and best practices

• Proven ability to gather and synthesize diverse data sources for actionable insights

Responsibilities:

• Develop advanced CECL credit loss models for stress-testing, reserving, and underwriting

• Personally code, test, and maintain these models to ensure they meet business and regulatory needs

• Create scalable data workflows using tools like Apache Airflow

• Drive impactful business insights with advanced dashboarding tools like Tableau or Qlik Sense

• Produce detailed reports and collaborate with risk management, audit, and regulatory teams