Location: Granadilla and San Carlos, Costa Rica
You will be part of a team turning data into actionable insights. You must have experience using a variety of data wrangling and analysis methods, with a variety of tools. You will validate data on entry and perform exploratory data analysis to propose the next steps in data cleansing and feature engineering. The decisions you help make about variable selection will be translated into data pipelines that feed the modeling and visualization processes. To do so, problem-solving and strong analytical skills are a must, as well as a strong understanding of statistics. You have to be curious and enthusiastic about data and have the necessary communication skills to explain your findings.
- Using exploratory data analysis, you will help identify cleansing, transformation, and integration priorities to prepare data for machine learning methods.
- Use data analysis to increase and optimize customer experiences, revenue generation, ad targeting, and other business outcomes.
- Develop processes and tools to monitor and analyze model performance and data accuracy.
- Maintain clear and coherent communication, both verbal and written, to understand data needs and report results.
Skills and Qualifications (Required)
- Good applied statistics skills, such as distributions, statistical testing, regression, maximum likelihood estimators, etc. Understanding when different techniques are (or aren’t) a valid approach. — Knowledge of advanced statistical techniques and concepts (regression, properties of distributions, statistical tests, and proper usage, etc.) and experience with applications.
- Experience with analysis libraries such as sci-kit-learn, pandas (Python), or dplyr (R) and their corresponding programming language (Python/R).
- Proficiency in using database query languages such as SQL.
- Strong problem-solving skills, oriented towards product delivery.
- Experience implementing and maintaining data analysis pipelines.
- Knowing how to deal with imperfections in data using data cleaning and data wrangling.
- Good English communication skills and a collaborative approach to sharing ideas and finding solutions.
- Team player, flexible, and creative.
- A critical attitude towards your work and deliveries.
- Ability to come up with solutions independently, even for abstract problems.
- Communication skills on describing findings, or the way techniques work to audiences, both technical and non-technical.
- Bachelor’s Degree in a scientific field that has provided experience with experimental design, data analysis, and reporting and/or 2-4 years of relevant work experience.
Preferred (Nice to have)
- Familiarity with Big Data or cloud environments (e.g. AWS, Google Cloud Platform, etc.).