Statistical Analysis Software And Predictive Modeling Specialist

What role will you play in the team

You will serve as a specialized quantitative modeler within our Data Science, Analytics & Machine Learning division, focusing on leveraging advanced statistical analysis software and rigorous econometric frameworks. Your core mission is to transform complex, multi-dimensional business datasets into actionable predictive insights, driving high-stakes strategic decisions and risk assessment models for our expanding enterprise client portfolio across multiple industrial sectors.

What you will do

You will develop, validate, and maintain sophisticated predictive models, hypothesis testing frameworks, and multivariate regression analyses utilizing SAS, SPSS, and Minitab. By collaborating closely with data engineering teams, you will clean, structure, and analyze large-scale datasets, ensuring absolute statistical rigor, data integrity, and compliance with institutional research standards before presenting findings to executive leadership.

Key responsibility

• Develop and execute advanced multivariate statistical models, time-series forecasting, and regression analyses using Statistical Analysis Software, SAS, SPSS, and Minitab.
• Perform rigorous exploratory data analysis (EDA) on large-scale structured datasets to identify underlying trends, anomalies, and statistically significant correlations.
• Design, execute, and evaluate controlled A/B testing frameworks and hypothesis testing experiments to measure business intervention impacts accurately.
• Translate complex quantitative findings and predictive modeling outputs into comprehensive, visually compelling executive dashboards and technical reports.
• Collaborate with database administrators to extract, transform, and load (ETL) large datasets from SQL and PostgreSQL repositories for analytical modeling.
• Ensure stringent data governance, validation, and documentation standards across all statistical models to maintain reproducibility and audit compliance.
• Continuously refine predictive algorithms and scoring mechanisms to improve accuracy, reduce false positives, and optimize operational efficiency.

Required Qualification and Skills

• Bachelor's or Master's degree in Statistics, Mathematics, Econometrics, Data Science, or an equivalent quantitative discipline.
• Possess 1 to 2 years of professional experience in applied statistical modeling, predictive analytics, or quantitative research roles.
• Advanced proficiency in Statistical Analysis Software, SAS, SPSS, Minitab, and Python or R for advanced data manipulation.
• Deep working knowledge of SQL and relational database management systems for extracting and querying complex data structures.
• Demonstrated expertise in probability theory, hypothesis testing, ANOVA, factor analysis, and advanced regression techniques.
• Exceptional verbal and written communication skills with a proven track record of presenting complex statistical insights to non-technical stakeholders.
• Strong organizational abilities, meticulous attention to detail, and the capability to manage multiple analytical projects simultaneously.

A Day in the Life

You start your morning by executing SAS scripts to process overnight batch data loads and evaluate the stability of our credit scoring predictive models. Mid-morning involves conducting an ANOVA analysis in SPSS to evaluate customer segmentation results for a new market campaign. After lunch, you collaborate with the data engineering unit to refine SQL queries extracting PostgreSQL records, and conclude your day drafting a comprehensive statistical validity report for the executive steering committee.