ML Engineer (Forecasting & Applied Data Science)

Experience and Skills

• 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

Key Responsibilities

• 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.

Benefits

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.

Nice to Have

• Power BI
• GIS
• Geospatial Analytics
• Survival Analysis
• Customer Segmentation

Niuro is hiring a Senior Machine Learning Engineer for an open position building production demand-forecasting models and customer-segmentation pipelines. You will work with marketing, retail, and pricing teams to deploy and monitor these models in cloud environments. In this role, you will bridge the gap between complex statistical modeling and business strategy, transforming commercial challenges in demand, pricing, and customer behavior into robust, production-ready machine learning solutions. As a senior member of the team, you will take ownership of end-to-end machine learning pipelines, ensuring high data quality and model reliability. You will collaborate closely with cross-functional business units, deploy scalable solutions in cloud environments, and mentor other data professionals to foster technical excellence and drive impactful decision-making.