Key responsibilities:

1. Apply statistical techniques to analyze and interpret data
2. Work on statistical models and their applications in predictive analytics
3. Effectively communicate statistical findings to both technical and non-technical stakeholders
4. Continuously learn and stay updated with advancements in statistical methods and tools used in data science

Requirements:

1. Basic knowledge of statistics and familiarity with statistical concepts such as probability, hypothesis testing, regression analysis, and statistical inference
2. Understanding of descriptive statistics and measures of central tendency and variability
3. Ability to apply statistical techniques to analyze and interpret data
4. Experience in working with statistical software or programming languages commonly used in data science(e.g Python, SPSS)
5. Knowledge of survey designing
6. Understanding of statistical models and their applications in predictive analytics
7. Ability to effectively communicate statistical findings to both technical and non-technical stakeholders
8. Strong critical thinking skills and the ability to solve complex problems using statistical analysis

The basic software to know:

1. Basics of Excel
2. Knowledge of making presentations using PowerPoint
3. Knowledge of Python programing language and machine learning algorithms

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