Data Scientist

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Data ScientistData

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Quick Summary

Overview

ABOUT US ARRISE sets the benchmark for service delivery and excellence in the iGaming industry. Playing a key role in the success of its clients,

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Data ScientistData

ARRISE sets the benchmark for service delivery and excellence in the iGaming industry. Playing a key role in the success of its clients, ARRISE helps to deliver exceptional gaming experiences to millions of players worldwide.

Our global team of over 10,000 talented and driven professionals are shaping the future of iGaming. Headquartered in Gibraltar, we have offices spanning Canada, India, the Isle of Man, Latvia, Malta, Romania, Serbia, Bulgaria, and the UAE, and more exciting destinations on the horizon.

At ARRISE, we take pride in creating growth opportunities at all levels, constantly investing in our people while welcoming new colleagues and forging strategic partnerships that open new opportunities for success.

To achieve this, we bet on ourselves. We know that success is a collective effort, and our team is driven by ambition, collaboration, and a shared commitment to grow and succeed — while embracing every step of the journey.

Be part of the future of iGaming with 10,000 ARRISERS! See a job that excites you? Apply now, and our friendly recruitment team will connect with you soon. Your journey starts here.

Responsibilities

~1 min read

→Design and develop advanced ML algorithms for image, text, audio, and tabular data
→Develop and optimize pipelines in Azure to train models across various domains
→Implement end-to-end applications in Python, including unit and integration tests
→Continuously monitor system performance and troubleshoot issues
→Collaborate with cross-functional teams to produce solutions to complex problems
→Develop common packages and tools for logging, model inference, and more

Bachelor's or Master's degree in Computer Science, Engineering, or a related field
Strong proficiency in Python, PyTorch, and TensorFlow
Proven experience in managing and analyzing large datasets
Solid understanding of foundational DL algorithms
Expertise in unit and integration tests (Pytest) and CICD pipelines
Experience with data versioning, model management, experiment tracking, key evaluation metrics, and optimization techniques
Extensive knowledge and hands-on experience in Docker
Solid understanding of traditional Computer Vision and classical ML
In-depth experience with computer vision models for object detection, image classification, and segmentation
Experience with Azure services (ML Studio, Data Factory, Functions, Blob Storage) or equivalent cloud provider services
Knowledge of AWS (Amazon Web Services) services, especially EC2 and S3
Experience with Huggingface Transformers, Elastic Stack, Gitlab CI pipelines
Experience with Prompt Engineering, Retrieval Augmented Generation (RAG), LLM frameworks (LangChain, LlamaIndex, Haystack, ...), and fine-tuning LLMs