Data Scientist (Machine Learning)

Location: Remote from Spain; candidates must already have the legal right to work in the EU

Salary: $3,500–$4,000 gross per month

Company

OnTarget Labs develops machine learning, analytics, and data science solutions for business customers.

What you will do

• Design and implement data science solutions across the project lifecycle.
• Analyze large-scale datasets to identify trends, anomalies, and actionable insights.
• Develop and optimize machine learning models, predictive workflows, and feature engineering pipelines.
• Lead data science activities for customer implementations, pilots, and production deployments.
• Collaborate with Product, Engineering, Customer Success, customers, and external partners to translate business needs into technical solutions.
• Deliver training, knowledge transfer, and recommendations for improving products, algorithms, and analytical capabilities.

Requirements

• Legal right to work in the EU immediately through an existing status is required; visa sponsorship and relocation support are not offered.
• High proficiency in English is required.
• Bachelor’s degree in Data Science, Computer Science, Mathematics, Statistics, Economics, or a related quantitative field.
• At least 2 years of experience in Data Science, Data Engineering, Machine Learning, or Big Data development.
• Strong programming skills in Python and experience with PySpark, Apache Spark, large-scale data processing, and machine learning pipelines.
• Experience with ML lifecycle and workflow management tools such as MLflow or Airflow, plus strong analytical and statistical modeling skills.

Nice to have

• Experience in financial services, fraud detection, risk analytics, compliance, or transaction monitoring.
• Familiarity with cloud-based data and machine learning environments.
• Experience with model deployment and monitoring, anomaly investigation, and high-volume datasets.
• Direct experience working with customers or external stakeholders.

Culture & Benefits

• Full-time remote work.
• Customer-facing work with cross-functional collaboration.
• Opportunity to work on scalable machine learning and analytics solutions.