Vacancy expired!
- Do exploratory data analysis on various data sets used by the team to deeply understand the quality, structure and the potential.
- Discover important, non-obvious patterns from the data and connect those to possible business actions and strategic choices.
- Help multiple audiences - engineers, product managers, executives - dig into and understand the output of your analyses using notebooks (e.g. Jupyter), visualization, presentations etc.
- Constantly look for and adopt new techniques and tools to ensure the team stays at the forefront of modern large-scale data processing and analysis techniques
- You have a strong academic background in statistics and data analysis. The typical candidate has a Bachelor's or Master's degree in Math, Statistics, Computer Science, or Physics or such quantitative fields or have done a program from a business school in marketing, analytics etc. with a focus on quantitative approaches.
- You are proficient in at least one programming language commonly used for data analysis (like R/Python), and cozy with SQL & data warehousing systems like MySQL, Amazon Redshift, BigQuery.
- Possess strong data visualization skills using programmatic tools (e.g. ggplot2, shiny, d3.js) and other visualization frameworks like victory, highcharts etc.
- You have at least 3 years of experience working with data and data analysis. You have worked with noisy real-world data involving a large number of variables, interactions and uncertainty.
- You have a good grasp of basic statistics and probability. You have done analyses where your focus was on explaining and understanding the underlying process, variable relationships, causality etc.
- Experienced in working with large data sets, with big data processing tools like Spark.
- Have data engineering skills to do basic preprocessing, cleaning and transformations.
- Experienced in designing and analyzing randomized controlled experiments
Vacancy expired!