ML Engineer (Forecasting & Applied Data Science)

Senior-level expertise with 5+ years of experience in Data Science or Machine Learning Engineering, with a strong focus on time series forecasting and predictive modeling.

C1 English level or higher.

Proficiency in Python or R for statistical modeling and machine learning.

Hands-on experience deploying and monitoring machine learning models in a major cloud environment, preferably GCP or Azure.

Strong statistical foundation, including experience with time series models, survival analysis, and customer segmentation.

Advanced SQL skills and experience working with relational databases.

Proven experience leading technical projects or mentoring junior data professionals.

Degree in Statistics, Engineering, Data Science, Mathematics, or a related quantitative field.

Hands-on experience with AWS, MLOps, Data Pipelines.

Skills

Python

R

SQL

Machine Learning

Time Series Forecasting

GCP

Azure

AWS

MLOps

Statistics

Data Pipelines

Design, develop, and maintain production-scale forecasting and time series models to predict demand and other key business metrics.

Build and optimize robust data pipelines to ensure the quality, availability, and traceability of models in production.

Collaborate with marketing, retail, and pricing teams to translate complex business requirements into actionable machine learning solutions.

Implement and monitor scalable MLOps practices within cloud environments to guarantee model performance and reliability.

Perform exploratory data analysis and customer segmentation using transactional, digital behavior, and geospatial data sources.

Document technical processes and communicate complex analytical results clearly to non-technical stakeholders.

Power BI

GIS

Geospatial Analytics

Survival Analysis

Customer Segmentation

We provide the opportunity to participate in impactful and technically rigorous industrial data projects that drive innovation and professional growth. Our work environment emphasizes technical excellence, collaboration, and continuous innovation.

Niuro supports a 100% remote work model, allowing flexibility in work location globally. We invest in career development through ongoing training programs and leadership opportunities, ensuring continuous growth and success.

Upon successful completion of the initial contract, there is potential for long-term collaboration and stable, full-time employment, reflecting our long-term commitment to our team members.

Joining Niuro means becoming part of a global community dedicated to technological excellence and benefiting from a strong administrative support infrastructure that enables you to focus on impactful work without distraction.