Data Scientist III

The Hershey Company; Guadalajara; A distancia; MXN 30,000 - 70,000; Jornada completa

Descripción de la vacante

Una empresa innovadora busca un Data Scientist III para liderar proyectos de ciencia de datos y aplicar técnicas avanzadas de análisis y aprendizaje automático. En esta posición remota, serás responsable de extraer información valiosa de grandes conjuntos de datos, diseñar modelos predictivos y colaborar con equipos multifuncionales para impulsar decisiones basadas en datos. Con un enfoque en la innovación y la mejora continua, tendrás la oportunidad de influir en la estrategia empresarial mediante el desarrollo de soluciones de inteligencia artificial. Si tienes pasión por la ciencia de datos y un deseo de marcar la diferencia, esta es la oportunidad perfecta para ti.

Formación

• 5+ years in quantitative research and machine learning.
• Experience with cloud-based analytical systems and deploying ML models.

Responsabilidades

• Lead data science projects using advanced analytics and machine learning.
• Collaborate with teams to develop AI products and solutions.

Conocimientos

Python

R

Machine Learning

Statistical Analysis

Data Visualization

SQL

Cloud Computing

Data Processing

Educación

Bachelor’s degree in Data Science or related field

Master’s degree or advanced certification

Herramientas

Azure Cloud

Databricks

Snowflake

Hadoop

Spark

MLflow

Azure DevOps

GitHub

Descripción del empleo

Data Scientist III (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 III will collaborate closely with cross-functional teams to identify opportunities, develop AI products, and deploy solutions that address complex business challenges.

Responsibilities / Outcomes

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

Project Leadership and Product Management

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

Communication and Collaboration

1. Communicate findings and recommendations to non-technical stakeholders.
2. 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, MongoDB, Azure SQL etc.).
• 2+ years of experience with large-scale data processing architecture (Hadoop, HIVE, Spark/SparkR, Snowpark etc.) are a plus.