Data Scientist / IA Engineer

Worldwide | Sept. 10, 2026

Report as Closed

Company: Lisit

Country: Worldwide

Salary: $18,000 - $24,000

Type: Remote

Employment: Full-time

Description: We create, develop and implement software services capable of providing required automation and optimization tools while maintaining a constant focus on innovation and passion for challenges.

At Lisit we design, develop and implement software services aimed at automating and optimizing processes. Our goal is to offer tools that allow clients to transform their operations with a constant focus on innovation and passion for challenges. The team promotes operational effectiveness through consultative support that integrates diverse tools and practices to achieve its objectives, through a comprehensive support and implementation strategy.

Training

University degree in Computer Engineering, Computer Engineering, Computer Science, Statistics, Mathematics, Industrial Civil Engineering or related careers.

Knowledge and/or experience

Exclusive experience in the following technologies:

Python (Pandas, NumPy, scikit-learn)
Frameworks Deep Learning (TensorFlow, PyTorch, Keras)
SQL and management of relational and non-relational databases. Ideal Postgresql.

Required Knowledge: Statistical modeling and supervised/unsupervised machine learning. Cleaning, transformation and exploratory data analysis (ETL/EDA). Gitlab. Experience in agile methodologies. JSON. Linux Medium Level. Consumption and integration of APIs.

Competencies and Skills:

Analytical and statistical thinking to draw conclusions from data.
Ability to translate business needs into data problems and models.
Teamwork and effective communication with business areas, Backend, QA and DevOps.
Ability to learn and adapt to new techniques, tools and trends in AI.
Rigor in model validation and data quality.
Knowledge of agile methodologies with SCRUM (not exclusive).

At Lisit we are looking for a Data Scients + General Background

In addition, defines data architectures and models, promotes good MLOps and data governance practices, and collaborates closely with Backend, Process, QA and DevOps teams to ensure that AI solutions are scalable, maintainable and aligned with the company's strategic objectives.

Responsible for designing, developing, training and putting analytical models into production, predictive and artificial intelligence that add value to the logistics business. Its main objective is to transform data into actionable information and intelligent solutions that optimize processes such as demand forecasting, route optimization, resource allocation, anomaly detection and improving customer experience.

Main Functions

Job Objectives

Responsible for designing, developing, training and putting into production analytical, predictive and artificial intelligence models that add value to the logistics business. Its main objective is to transform data into actionable information and intelligent solutions that optimize processes such as demand forecasting, route optimization, resource allocation, anomaly detection and improving customer experience. Additionally, define data architectures and models, promote good MLOps and data governance practices, and collaborate closely with Backend, Process, QA and DevOps teams to ensure that AI solutions are scalable, maintainable and aligned with the company's strategic objectives.

Collect, clean, transform and analyze large volumes of data from different sources in the logistics ecosystem.
Perform exploratory data analysis (EDA) and identify patterns, trends and opportunities for improvement.
Design, develop, train, validate and optimize machine learning and artificial intelligence models.
Deploy models in production and monitor their performance, ensuring their retraining and continuous improvement (MLOps).
Build and expose services and APIs for the integration of models with business applications.
Collaborate with DevOps teams in the definition of data and deployment pipelines. (CI/CD).
Document methodologies, assumptions, technical decisions and model results to facilitate collaboration and traceability.
Communicate findings and recommendations to business areas through visualizations and clear reports.

Work History / Knowledge that adds points

Postgraduate degrees, diplomas or certifications in Data Science, Machine Learning, Artificial Intelligence or related areas (optional, but valued).

Experience in logistics projects, transportation, route optimization, demand forecasting is desirable.

Apply here:

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