Senior Machine Learning Engineer – Customer Analytics & Recommendation Systems

Project overview

This contract role in Helsinki focuses on building and deploying machine-learning solutions for customer churn, propensity, lifetime value, and next-best-action recommendations. The core requirements include Python, SQL, PySpark, model development and validation, feature and label engineering, AWS S3 with data-lake or lakehouse architecture, MLOps, and NLP modeling; Apache Iceberg or Delta tables and Dremio are also named in the technical requirements.

The work includes point-in-time-correct datasets, predictive pipelines, recommendation ranking, and model performance checks across customer segments and time periods. The structured input gives an experience band of 6–8 years, while the description says 5 years; this summary uses 6–8 years as the structured band and notes the discrepancy. Helsinki is specified, but the work mode is not; Finnish citizenship or at least three years of continuous Finnish residency is stated as the security-clearance eligibility criterion.

Requirements

• Python programming
• SQL
• PySpark
• Machine-learning model development, training, and validation
• Feature engineering and target or label creation
• AWS S3 and data-lake or lakehouse architecture
• Apache Iceberg or Delta tables and Dremio
• MLOps using Kubeflow, MLflow, SageMaker, or equivalent
• NLP modeling and sentiment-based feature development
• Customer churn, propensity, customer lifetime value, and recommendation modeling

Project details

• Start: flexible
• Remote: onsite
• Location: Finland, FI