Job Details

Data Scientist

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Growth Acceleration Partners LATAM






Curidabat, Cartago and San Carlos, Costa Rica


Software and Programming




Job Overview

You will be part of a team turning data into actionable insights using algorithms and machine learning. 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 next steps in data cleansing and feature engineering. The decisions that 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. We are seeking a Data Engineer with a versatile skill set to help our data-driven customers succeed.


  • Using exploratory data analysis, you will help identify cleansing, transformation and integration priorities to prepare data for machine learning methods.

  • You will work on and maintain data pipelines, for feature engineering, data transformation, and data enrichment.

  • Use predictive modeling 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.

  • Stay up to date on developments in machine learning and data analysis techniques.

  • 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.

  • Basic understanding of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and their real-world advantages/drawbacks.

  • Experience with analysis libraries such as scikit-learn, pandas (Python) or dplyr (R) and their corresponding programming language.

  • 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.

  • 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)

  • Experience with data visualization frameworks or libraries (matplotlib, seaborn, ggplot2).

  • Experience with machine learning frameworks such as tensorflow, keras and torch.

  • Communication skills on describing findings, or the way techniques work to audiences, both technical and non-technical.

  • Proficiency in using database query languages such as SQL.

  • Familiarity with Big Data or cloud environments (e.g. AWS, Google Cloud Platform, etc.).

  • Experience in predictive analytics using statistical modeling techniques to conduct forecasting.

  • Experience in advanced analytics techniques in a consulting environment and not solely in an academic environment.