Applied Data Scientist: ML, Statistics & Modeling

Crossing Hurdles; Canada; Presencial; CAD 90.000 - 120.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Health insurance

Descripción de la vacante

Crossing Hurdles is seeking a data scientist to design and execute statistical analyses, uncover actionable insights from complex datasets, and develop robust ML models.

You will apply data modeling techniques and manage large-scale data transformations using Python and Pandas, collaborating with stakeholders to define experiments.

This role requires excellent written and verbal communication to document methodologies, findings, and recommendations with clarity and precision.

Formación

• Strong experience in applied statistics, experimental design, and ML.
• Expertise with Python and libraries Pandas and scikit-learn.
• Proven ability to develop, tune, evaluate ML models in practical settings.
• Strong data modeling for structured and unstructured data.
• Excellent written and verbal communication; documentation.

Responsabilidades

• Design and execute statistical analyses to uncover actionable insights from complex datasets.
• Develop and validate machine learning models for various business or research objectives.
• Apply data modeling techniques and manage large-scale data transformations using Python and Pandas.
• Collaborate with stakeholders to define experimentation frameworks and analyze outcomes.
• Document methodology, findings, and recommendations with a focus on clarity and precision.
• Review peer contributions and provide high-quality feedback to support knowledge sharing.

Conocimientos

Applied statistics

Experimental design

Machine learning

Communication skills

Herramientas

Python

Pandas

scikit-learn

Data modeling

Descripción del empleo

Crossing Hurdles is seeking a data scientist to design and execute statistical analyses, uncover actionable insights from complex datasets, and develop robust ML models.

You will apply data modeling techniques and manage large-scale data transformations using Python and Pandas, collaborating with stakeholders to define experiments.

This role requires excellent written and verbal communication to document methodologies, findings, and recommendations with clarity and precision.