Remote Python Data Scientist (Scikit-Learn)

Jamefy; Colombia; Remote; COP 289,911,000 - 483,185,000; Full time

Benefits offered by this job

100% remote work

Compensation in USD or local currency

Home office hardware and software

Flexible hours

Paid parental leave and vacations

Multicultural global team

Mentorship and growth opportunities

Job summary

BairesDev is hiring a Python Data Scientist to design, develop, and deploy advanced machine learning models for real-world business problems. You will turn raw data into actionable insights, driving data-informed decision-making across projects.

You will collaborate with cross-functional teams to productionize models, optimize performance, and ensure scalable, reliable solutions in a fully remote environment.

Qualifications

• 5+ years of experience in Data Science or Machine Learning.
• Advanced proficiency in Python and machine learning libraries like Scikit‑learn.
• Proven expertise in data preprocessing, feature engineering, and building predictive models.
• Advanced proficiency in English.

Responsibilities

• Design, build, and optimize robust machine learning models for predictive analytics.
• Conduct comprehensive data cleaning, preprocessing, and exploratory data analysis.
• Perform advanced feature engineering to improve model accuracy and performance.
• Collaborate with engineering and product teams to integrate models into production environments.
• Evaluate model metrics and tune hyperparameters to ensure scalability and reliability.

Skills

Python

English proficiency

Feature engineering

Data preprocessing

Model evaluation

Education

5+ years Data Science / ML experience

Tools

Scikit-learn

Job description

BairesDev is hiring a Python Data Scientist to design, develop, and deploy advanced machine learning models for real-world business problems. You will turn raw data into actionable insights, driving data-informed decision-making across projects.

You will collaborate with cross-functional teams to productionize models, optimize performance, and ensure scalable, reliable solutions in a fully remote environment.