Statistics / Data Analytics Associate

Are you seeking an exciting opportunity to join a dynamic and growing team in a fast-paced and intellectually stimulating environment? This is a unique chance for you to work as a Statistics and Analytics Professional within the CO&D WKO Data Management team. Utilize your expertise in statistical techniques to deliver actionable insights and support data-driven decision-making. Join us and become part of a team that values innovation, analytical rigor, and excellence in quantitative research and data analysis.

Job Summary

As a Statistical Data Analyst within the Commercial & Investment Bank, you will be responsible for designing, executing, and interpreting statistical analyses to support business decision-making. You will work with large and complex datasets to uncover trends, test hypotheses, and provide actionable insights that drive strategic initiatives. Your role involves applying advanced statistical techniques, building predictive models, and ensuring the rigor and accuracy of all analyses.

You will collaborate closely with business partners, data engineers, and other analysts to translate business questions into statistical problems and deliver clear, concise results. You will be expected to write clean, reusable code in R or Python for data analysis, automate statistical workflows, and document methodologies to ensure transparency and reproducibility.

Job responsibilities

• Apply statistical techniques such as regression, hypothesis testing, time series analysis, and clustering to analyze business data and uncover insights.
• Calculate descriptive statistics including mean, median, mode, variance, standard deviation, and percentiles to summarize data characteristics.
• Conduct inferential statistical analyses using hypothesis testing, confidence intervals, p-values, t-tests, chi-square tests, and ANOVA.
• Utilize probability theory by working with probability distributions, Bayes’ theorem, and random variables to model uncertainty.
• Perform regression analysis with linear, logistic, and multivariate models, including thorough model diagnostics.
• Implement sampling methods such as simple random, stratified, and cluster sampling, and determine appropriate sample sizes.
• Analyze time series data for trends, seasonality, and forecasting using ARIMA and related models.
• Demonstrate proficiency in R, Python (NumPy, pandas, SciPy, statsmodels), SAS, SPSS, and Stata for statistical analysis.
• Partner with business stakeholders to translate business questions into structured analyses and actionable recommendations.
• Clean, organize, and validate data to ensure the accuracy and reliability of analytical results.

Develop dashboards and reports in Tableau for effective data visualization and business consumption, and use Python for advanced analytics and automation.

Required qualifications, capabilities, and skills

Preferred qualifications, capabilities, and skills :