8 hours ago

Data Scientist

ARRISE

Hybrid
Full Time
$120,000
Hybrid

Job Overview

Job TitleData Scientist
Job TypeFull Time
Offered Salary$120,000
LocationHybrid

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Job Description

About ARRISE

ARRISE sets the benchmark for service delivery and excellence in the iGaming industry. Playing a key role in the success of its clients, which include Pragmatic Play, a brand relied upon by the world’s biggest online casinos for its cutting-edge products, 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.

What You'll Be Doing as a Data Scientist

  • 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

What We Ask Of You

  • 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

Key Skills/Competency

  • Machine Learning
  • Deep Learning
  • Python
  • Azure
  • PyTorch
  • TensorFlow
  • Computer Vision
  • LLM Frameworks
  • CICD Pipelines
  • Docker

Tags:

Data Scientist
Machine Learning
Deep Learning
Data Analysis
Algorithm Development
Model Optimization
System Monitoring
Troubleshooting
Collaboration
Solution Development
Experiment Tracking
Python
PyTorch
TensorFlow
Azure
Docker
Pytest
CICD
Computer Vision
LLMs
Gitlab CI

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How to Get Hired at ARRISE

  • Research ARRISE's culture: Study their mission, values, recent news, and employee testimonials on LinkedIn and Glassdoor.
  • Tailor your resume: Highlight your Python, ML, Azure, and Deep Learning expertise relevant to the Data Scientist role.
  • Showcase iGaming interest: Demonstrate understanding of the iGaming industry and ARRISE's impact on client success like Pragmatic Play.
  • Prepare for technical interviews: Expect questions on ML algorithms, Python, PyTorch, TensorFlow, Azure, and data pipeline optimization.
  • Emphasize collaboration and problem-solving: Be ready to discuss how you've worked in cross-functional teams to deliver complex data solutions.

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