Principal Data Scientist

Principal Data Scientist

Asad Hameed

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Topics we cover!
1 Key Responsibilities
2 Required Skills and Qualifications
3 Desired Skills (Good-to-Have)
4 Benefits
5 How to Apply

Royal Cyber Inc. is a dynamic leader in delivering innovative digital transformation solutions, and we are looking for an experienced Principal Data Scientist to join our rapidly growing team. The ideal candidate will possess extensive experience in computer vision, deep learning, and generative AI techniques. As the Principal Data Scientist, you will lead the development of advanced AI-driven solutions, harnessing cutting-edge technologies and delivering high-impact results.

Key Responsibilities

  • Model Development & Optimization: Design, develop, and deploy cutting-edge computer vision models for image and video analysis. You will leverage traditional and generative AI techniques (such as GANs, diffusion models, etc.) to enhance functionality and accuracy.
  • Generative AI Integration: Implement frameworks such as GANs and VAEs to generate synthetic data for model training, driving improvements in data augmentation and resolving complex computer vision problems.
  • Data Analytics & Insights: Conduct advanced data analytics to extract actionable insights from image and video data. Use these insights to inform the model development cycle and improve outcomes.
  • End-to-End Machine Learning: Lead the implementation of comprehensive machine learning pipelines for computer vision tasks using platforms like TensorFlow, PyTorch, and related tools.
  • Cloud & Scalability: Work closely with engineers to ensure the seamless integration of AI models into cloud environments like AWS, Azure, or Google Cloud, optimizing for scalability and production-readiness.
  • Model Evaluation & Performance Tuning: Continuously evaluate model performance, applying optimization techniques to ensure superior accuracy and operational efficiency in production settings.
  • Research & Innovation: Stay abreast of the latest advancements in deep learning, computer vision, and generative AI. Apply this knowledge to drive innovative solutions for complex challenges.
  • Mentorship & Knowledge Sharing: Provide mentorship and guidance to junior team members, fostering a collaborative, learning-driven culture in the field of AI and machine learning.

Required Skills and Qualifications

  • Experience: At least 6+ years of professional experience in the Data Science field, specializing in computer vision, deep learning, and generative AI.
  • Technical Expertise:
    • Strong proficiency in tools and libraries such as Python, OpenCV, Scikit-learn, TensorFlow, PyTorch, and Keras.
    • Demonstrated expertise in designing and implementing machine learning models for computer vision tasks (e.g., object detection, image segmentation, tracking).
  • Generative AI: Hands-on experience with generative AI frameworks, including GANs (Generative Adversarial Networks) and VAEs (Variational Autoencoders).
  • Cloud Platforms: Experience working with cloud-based platforms like Azure, AWS, or Google Cloud is crucial for deploying scalable machine learning systems.
  • Data Analytics & Preprocessing: Ability to perform data analytics, including feature engineering, exploratory data analysis (EDA), and experience with image/video preprocessing techniques (e.g., augmentation, normalization, segmentation).
  • Advanced Knowledge:
    • Familiarity with big data technologies such as Hadoop, Spark, Kafka is desirable.
    • Advanced understanding of mathematics, statistics, optimization, and algorithmic design as they apply to deep learning and generative AI.
  • Soft Skills: Strong communication and collaboration skills to work effectively with cross-functional teams, including engineers, product managers, and business stakeholders.

Desired Skills (Good-to-Have)

  • 3D Computer Vision: Experience with 3D computer vision tasks such as point cloud analysis and depth estimation.
  • Advanced Data Visualization: Proficiency in data visualization tools like Matplotlib, Seaborn to represent results and data insights in an impactful way.
  • Model Deployment: Experience with deploying computer vision models in cloud environments (AWS, Google Cloud, or Azure).

Benefits

  • Competitive Compensation: Attractive salary package based on skills and experience.
  • Remote Work Flexibility: Enjoy working remotely with flexibility.
  • Learning & Growth: Opportunity to work on innovative AI-driven projects, and ample opportunities for skill development and career advancement.
  • Global Collaboration: Collaborate with cross-functional teams and contribute to impactful projects with a global reach.
  • Work-Life Balance: Structured work timings (03 PM to 12 AM), allowing flexibility and a healthy work-life balance.

How to Apply

Interested candidates are encouraged to submit their updated CV along with a portfolio (if applicable) showcasing their relevant projects and experience.

Please send your CV and other supporting documents to careers@royalcyber.com or apply online through our website.

Asad Hameed
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