Data Scientist

Llamabara; Lima Metropolitana; On-site; PEN 60,000 - 120,000; Full time

Benefits offered by this job

Permanent employment contract (full‑dr

Job summary

Llamabara in Lima, Peru is seeking a Data Scientist (Mid/Senior) to join our Data & Analytics team and translate large-scale data into business impact.

You will design, validate, and deploy ML models for risk, customer analytics, and revenue optimization; perform EDA, feature engineering, and build dashboards. Collaboration with Product, Operations, and Business units is essential, with emphasis on reproducibility and scalable pipelines.

Qualifications

• Bachelor's in Computer Science, Statistics, Mathematics, Engineering, or related field.
• 3+ years of experience in Data Science, Machine Learning, or Analytics.
• Experience with large datasets (1M+ records per day).
• Strong programming skills in Python and SQL.
• Solid understanding of ML algorithms and BI tools.

Responsibilities

• Perform Exploratory Data Analysis (EDA) to understand data structure and quality.
• Design, validate, and deploy ML models for risk management and analytics.
• Perform advanced feature engineering using historical and real-time data.
• Automate data workflows and scoring pipelines for scalability.
• Build dashboards/visualizations (Tableau/PowerBI) to communicate insights.
• Collaborate with cross-functional teams to deliver data-driven solutions.
• Ensure data quality through validation, monitoring, and cleansing.
• Research and experiment with new ML techniques and tools.
• Document analysis, features, and models for reproducibility.

Skills

Python

SQL

Pandas

Numpy

Tableau

PowerBI

Git

AWS

GCP

Spark

Hadoop

BigQuery

A/B testing

Causal inference

Education

Bachelor's in Computer Science

Tools

Tableau

PowerBI

Python

SQL

Git

AWS

GCP

Spark

BigQuery

Job description

About the Role

We are looking for a Data Scientist (Mid/Senior) to join our Data & Analytics team. You will work with large-scale datasets, design and deploy predictive models, and uncover insights that drive business impact. This role is ideal for someone passionate about applied machine learning, eager to translate data into tangible outcomes, and ready to thrive in a fast-paced environment.

• Perform Exploratory Data Analysis (EDA) to understand data structure, quality, and relationships, ensuring relevant features are used for model development.
• Design, validate, and deploy ML models for risk management, customer analytics, and revenue optimization.
• Perform advanced feature engineering using historical and real-time data.
• Automate data workflows and scoring pipelines for scalability.
• Build dashboards and visualizations (Tableau/PowerBI) to communicate insights to stakeholders.
• Conduct exploratory and statistical analysis to identify patterns and business opportunities.
• Collaborate with cross-functional teams (Product, Operations, Business) to deliver data-driven solutions.
• Ensure data quality through validation, monitoring, and cleansing processes.
• Research and experiment with new ML techniques and tools to keep solutions state-of-the-art.
• Document data analysis, feature engineering steps, and model development to ensure reproducibility, transparency, and knowledge sharing across teams

What we offer

• End-to-end exposure to production-grade ML model development.
• Opportunity to work on high-impact projects with multicultural teams.
• A collaborative and innovative environment where data drives decisions.
• Permanent employment contract (full payroll).
• Hybrid work model after the onboarding period (Lima: San Isidro)
• Access to company-paid trainings and certifications.
• Team-building activities and integration events.

Job requirements

• Bachelor’s in Computer Science, Statistics, Mathematics, Engineering, or related field.
• 3+ years of experience in Data Science, Machine Learning, or Analytics.
• Experience working with large datasets (1M+ records per day).
• Strong programming skills in Python (pandas, numpy, etc.) and SQL.
• Solid understanding of ML algorithms (classification, regression, ensemble methods).
• Hands-on experience with BI tools (PowerBI/Tableau) and version control (Git).
• Experience with cloud platforms (AWS/GCP) and distributed systems (Spark/Hadoop/BigQuery) is a plus.
• Familiarity with A/B testing, causal inference, and production-level ML deployment is desirable.
• Strong analytical mindset, communication skills, and problem-solving abilities.