Offer summary

Qualifications:

Bachelor’s degree in Data Science, Computer Science, Mathematics, Statistics, or similar; Master’s degree preferred., 5+ years of experience in quantitative research and machine learning applications., Proficient in programming languages such as Python and/or R, with experience in SQL and cloud platforms., Familiarity with machine learning frameworks and large-scale data processing architectures..

Key responsibilities:

Lead and execute data science projects to derive actionable insights and deliver business value.

Apply advanced statistical analysis and machine learning techniques to large datasets.

Collaborate with cross-functional teams to define product vision and integrate models into production systems.

Communicate findings and recommendations to stakeholders and identify opportunities for leveraging data science.

Job description

(Remote Position in México)

#Of Vacancy: 1

The Data Scientist III plays a crucial role in driving data-driven decision-making and innovation across the organization. The primary responsibility of the Data Scientist III is to lead and execute data science projects, leveraging advanced analytics techniques, machine learning models and Artificial Intelligence to derive actionable insights and deliver business value. The Data Scientist II will collaborate closely with cross-functional teams to identify opportunities, develop AI products, and deploy solutions that address complex business challenges.

Responsibilities / Outcomes

Data Analysis and Modeling

- Apply advanced statistical analysis and machine learning techniques to extract insights from large, complex datasets.
- Conduct exploratory data analysis to understand underlying patterns and relationships in the data.
- Design, develop and deploy predictive models, optimization systems, and other machine learning products.
- Interpret model outputs and communicate findings to stakeholders in a clear and actionable manner.
- Document methodologies, assumptions, and limitations of models following industry best practices.
- Collaborate with data engineers and data architects to integrate models into production systems.

Project Leadership and Product Management

Lead end-to-end data science projects and products, ensuring alignment with business objectives and stakeholder requirements.
Collaboratively define the product vision, backlog, and acceptance criteria with the agile team and subject matter experts.

Communication and Collaboration

Communicate findings and recommendations to non-technical stakeholders.
Collaborate with business leaders to identify opportunities for leveraging data science to drive strategic initiatives.

Knowledge, Skills & Abilities

Proficient in programming languages such as Python and/or R.
Azure Cloud platform experience preferred.
Intermediate level in SQL and experience with large-scale data processing architectures (Hadoop, HIVE, Spark/SparkR, Snowpark etc.).
Experience working with version control systems like Azure DevOps or GitHub.
Experience working with Databricks and MLflow is a plus.
Snowflake (nice to have)
Experience in the use of libraries for the development of web applications such as Shiny, Streamlit, Dash or Flask is good to have

Experience & Education

Education: Bachelor’s degree in Data Science, Computer Science, Mathematics, Statistics, Actuarial Science or similar. Master’s degree or advanced certification preferred.
5+ years of professional experience with applying quantitative research in optimizing human decisions using technologies like machine learning and/or deep learning.
2+ years of experience working with cloud-based analytical systems (e.g., AWS, Azure, Google Cloud).
2+ years of experience deploying ML models and AI solutions using platforms such as Databricks, Snowflake, Azure ML or AWS Sagemaker.
Proficient in machine learning frameworks (e.g., TensorFlow, Pytorch, scikit-learn, tidymodels etc.
2+ years of experience working with relational/non-relational databases (e.g., SQL Server, MySQL, mongo DB, Azure SQL etc.).
2+ years of experience with large-scale data processing architecture (Hadoop, HIVE, Spark/SparkR, Snowpark etc.) are a plus.

Required profile