Data Scientist Position

Start Date: Week 2, January

End Date: End of July 2026

Responsibilities:

• Design and train machine learning models to transform data into smarter decisions and AI solutions.
• Uncover valuable insights and drive innovation by exploring new technologies, data sources, and methodologies.
• Collaborate with product teams and stakeholders such as marketing and operations to shape data-driven products from concept to execution.
• Elevate analytical capabilities within the organization.

Required Qualifications and Experience:

• Proficiency in programming languages such as Python, R, SQL, and Java.
• Familiarity with database management systems like MySQL and PostgreSQL.
• Experience with big data technologies, including platforms like Hadoop and Spark.
• Strong skills in statistical analysis, including hypothesis testing, regression analysis, and time series forecasting.
• Expertise in data wrangling, including data cleaning, transformation, and ETL processes.
• Ability to develop predictive models for various banking-specific use cases such as credit scoring, email routing, fraud detection, and customer segmentation.
• Proficiency in quantitative analysis and data visualization tools like Power BI.
• Understanding of banking operations, products, services, and regulations.
• Knowledge of risk management and the ability to integrate it into data analyses.
• Ability to transform data insights into actionable business strategies.
• Strong communication skills to present findings to non-technical stakeholders.
• Effective collaboration with departments such as IT, marketing, and finance.
• Innovative problem-solving skills for complex data challenges.
• Commitment to continuous learning in the rapidly evolving field of data science.
• Ethical judgment regarding data privacy, fairness, and biases in modeling.
• Understanding of regulatory compliance, including financial regulations like Basel III, GDPR, and CCPA.
• Insights into customer analytics, including behavior, segmentation, lifetime value, and churn prediction.
• Familiarity with version control tools like Git.
• Knowledge of data warehousing solutions such as Wherescape, Snowflake, Redshift, or BigQuery.