Job Description: We are seeking an experienced Data Scientist with a strong focus on Recommender Systems. In this role, you will be responsible for designing, developing, deploying, and monitoring of advanced recommender systems that cater to our diverse user base. Key responsibilities:
Design and develop algorithms to deliver tailored recommendations to our user base.
Improve the efficiency and scalability of recommendation systems to handle large volumes of data and ensure fast response times.
Conduct rigorous A/B testing to validate and iterate recommender models.
Efficiently handle and integrate data from various sources, including APIs, databases, and Google Analytics.
Collaborate with cross-functional teams across data and engineering to produce solutions to complex problem statements.
Continuously monitor system performance, troubleshoot issues, and implement improvements/optimizations.
Create and maintain dashboards that provide actionable insights.
Stay updated with the latest trends and advancements in recommender systems.
Required Skills and Qualifications:
Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
Strong proficiency in Python, with extensive experience in PyTorch and/or TensorFlow.
Proven experience in managing and analysing large datasets.
Solid understanding of relational and NoSQL databases.
In-depth experience with Retrieval, Ranking, Batch, Live and Sequential recommendations.
Knowledge of architectures for recommenders such as Two-Tower, DLRM, DCN.
Experience with NVIDIA Merlin, TensorFlow Recommenders, NVTabular.
Experience with unit and integration tests (Pytest) and CICD pipelines.
Experience with data versioning, model management, experiment tracking.
Familiarity with key recommender metrics and optimization techniques.
Extensive knowledge and hands-on experience in Docker.
Excellent problem-solving, analytical, and communication skills.
Nice to Have:
Experience with distributed computing - Spark and / or Dask, or other technologies.
Experience with Azure services such as ML Studio, Data Factory, Functions, Blob Storage (or any other cloud provider equivalent services).
Knowledge of AWS (Amazon Web Services) services, especially EC2 and S3.
Familiarity with Data Validation tools (Great Expectation, ...)
Experience with A/B testing, and knowledge of associated metrics.
Experience in integrating and using Google Analytics data for recommender systems.
Experience with distributed training of recommender systems.
What we give you in return:
We offer a highly competitive salary.
A detailed company training on highest standards.
A chance to work in friendly and supportive culture.
Tremendous growth opportunities in a large fast moving international company.
About us: ARRISE powers Pragmatic Play, a leading supplier of player-favourite content to the iGaming industry. We are a software development and services company delivering end-to-end digital solutions. Headquartered in Gibraltar with offices around the world, including Malta, Romania, India, Canada, and Bulgaria, we are a global team of over 4,000 talented individuals with decades of experience across multiple industries and professions. Together, we form a cross-functional powerhouse that is driven to deliver. If you are a passionate and self-driven Data Scientist, we would love to hear from you. Join us at ARRISE powering Pragmatic Play and contribute to the development of cutting-edge gaming solutions that redefine the iGaming experience. To apply, please submit your resume detailing your relevant experience and interest in the position.
