Tech Data Scientist - RecSys Remote, Portugal 4d ago

Arrise; Portugal; A distancia; EUR 70.000 - 100.000; Jornada completa

Descripción de la vacante

Arrise is seeking an experienced ML Engineer to design end-to-end recommendation pipelines and scalable ETL workflows. You will develop, evaluate, and improve models for next-item prediction, integrating multi-modal signals and ensuring production-grade reliability.

Join a remote role based in Portugal, with a focus on cloud-based deployment, A/B testing, and data-driven product decisions across large data volumes.

Formación

• Bachelor's or Master's degree in Computer Science, Engineering, or related field.
• Strong Python experience with data science libraries and ML frameworks.
• Experience building and deploying end-to-end ML systems on cloud platforms.
• Strong understanding of deep learning-based recommender systems.
• Experience with unit/integration testing, CI/CD, and Docker.

Responsabilidades

• Design, implement, and optimize end-to-end recommendation pipelines.
• Build and maintain scalable ETL pipelines for data flows.
• Develop, evaluate, and improve ML models for recommendations.
• Research SOTA approaches to improve quality and metrics.
• Scale data/model pipelines for large data and real-time/batch processing.
• Integrate multi-modal data from various systems into models.
• Ensure robustness with unit and integration tests across data, modeling, deployment.
• Monitor system performance including pipelines and model quality.
• Design and analyze A/B tests to evaluate model performance.
• Build dashboards and observability tools for KPIs and health.
• Collaborate with Data/SW Engineers and stakeholders for production-ready solutions.

Conocimientos

Strong Python experience

Deep learning for recommender systems

Experience with ML systems in cloud

Testing and CI/CD

Data transformation and SQL

Educación

Bachelor's or Master's in CS/Engineering or related

Herramientas

Pandas

Polars

NumPy

scikit-learn

PyTorch

TensorFlow

JAX

Hugging Face

Azure

AWS

GCP

SQL

NoSQL

Descripción del empleo

• Design, implement, and optimize end-to-end recommendation pipelines, from data ingestion to model inference.


• Build and maintain scalable ETL pipelines to support reliable and efficient data flows.


• Develop, evaluate, and continuously improve ML models for recommendation systems.


• Research, prototype, and implement state-of-the-art (SOTA) approaches to improve recommendation quality and drive key business metrics.


• Scale and optimize data and model pipelines to handle large volumes of data and real-time or batch processing needs.


• Integrate multi-modal data (e.g., behavioral, transactional, and contextual signals) from various systems into recommendation models.


• Ensure robustness and stability of pipelines by implementing unit and integration tests across data, modeling, and deployment workflows.


• Monitor and maintain end-to-end system performance, including data pipelines, model quality, and downstream impact.


• Design and analyze A/B tests to evaluate model performance and support data-driven product decisions.


• Build dashboards and observability tools to track model metrics, system health, and business KPIs.


• Collaborate closely with Data Engineers, Software Engineers, and stakeholders to deliver scalable, production-ready solutions.

What you bring

• Bachelor's or Master's degree in Computer Science, Engineering, or a related field


• Strong Python experience with recent production use, including hands-on work with data science and machine learning libraries and frameworks (e.g., Pandas, Polars, NumPy, scikit-learn, PyTorch, TensorFlow, JAX, Hugging Face)


• Experience building and deploying end-to-end machine learning systems on cloud AI platforms (Azure, GCP, or AWS), from ETL pipelines to deployment and monitoring, including model versioning and experiment tracking, supporting either batch or real-time workflows.


• Strong understanding of deep learning-based recommender systems for next-item prediction, and analogous NLP architectures that model sequential patterns and context


• Demonstrated experience building efficient data transformation pipelines for both transactional (OLTP) and analytical (OLAP) workloads, with strong knowledge of SQL and NoSQL databases (e.g., PostgreSQL, MySQL, Redshift, Snowflake, BigQuery, MongoDB, Cassandra)


• Experience with unit and integration testing (e.g., Pytest), CI/CD pipelines, and Docker-based containerization

What sets you apart

• Experience building large-scale recommender systems (e.g., candidate generation, ranking, retrieval, personalization).


• Track record of publications in deep learning at relevant conferences or journals.


• Experience with Azure Data Factory / AWS Glue / Google Cloud Dataflow.


• Experience designing and analyzing A/B tests, with a solid understanding of relevant evaluation metrics.


• Experience designing and implementing metadata-driven pipelines to scale automated A/B testing systems.


• Experience developing multi-modal models that integrate multiple data types (e.g., text, images, audio).


• Experience applying transformer-based models or large language models (LLMs) to recommendation or personalization tasks.


• Experience with distributed training, including data parallelism and model parallelism.


• Experience with distributed data processing and big data technologies (e.g., Spark, Hadoop, Flink, Kafka, Hive, Presto, Databricks).

About us

ARRISE is a global leader in software development and services for the iGaming industry, bringing together more than 2,500 professionals operating across more than 12 locations worldwide.

From concept through to delivery, we combine technical expertise, creativity and industry knowledge to develop products, platforms and services that shape player experiences and support some of the industry's leading brands.

We are best known for the work we deliver for Pragmatic Play, creating and supporting technology, products and specialists services enjoyed by millions of players worldwide.

ARRISE is the company behind the games, the presenters, the studios and the platform 2,500+ people across 12 countries build and run the live entertainment that millions of players see every day.

We hire people to own their work. If you need a brief for every decision, this will not suit you. If you want the room to make the call and the accountability that comes with it, it will.

Frequently asked questions

Where is this role based?

This role is based in Remote, Portugal and follows a remote working pattern.

The working language for this role is English.

Can I ask for an adjustment during the hiring process?

Yes. If you need an adjustment at any stage of the process, tell your recruiter and we will arrange it.

Are there other open roles at ARRISE?

Yes. You can search every open role by team, location and working pattern on our careers page.

ARRISE is an equal opportunity employer. We consider every applicant on merit, regardless of age, disability, gender identity, marital status, pregnancy, race, religion, sex or sexual orientation. If you need an adjustment at any stage of the process, tell your recruiter and we will arrange it.