Data Scientist Job at Qode, Texas

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  • Qode
  • Texas

Job Description

Role Summary

We are seeking a highly skilled Lead Data Scientist / Senior Machine Learning Engineer to join our AI/ML and Advanced Analytics team. In this role, you will drive the development and deployment of cutting-edge machine learning, deep learning, and Generative AI solutions to solve complex business problems across Verizon’s business units. You’ll collaborate with cross-functional teams to deliver intelligent systems that scale, are responsible, and deliver measurable business impact.

Key Responsibilities

  • Design, develop, and deploy production-grade machine learning and deep learning models for predictive analytics, NLP, and computer vision use cases.
  • Lead the research and application of Generative AI (LLMs, diffusion models, multimodal models) to build innovative solutions in customer service, marketing, network optimization, and operations.
  • Collaborate with stakeholders to identify high-impact opportunities and formulate AI-driven strategies.
  • Guide and mentor junior data scientists and engineers; set best practices in modeling, data engineering, and MLOps.
  • Design and lead end-to-end ML pipelines using tools like TensorFlow, PyTorch, scikit-learn, MLflow, and Kubernetes.
  • Optimize models for performance, explainability, and fairness.
  • Stay up to date with state-of-the-art research in ML/AI and rapidly prototype solutions to test new ideas.
  • Contribute to the company’s IP portfolio by publishing whitepapers or filing patents.

Preferred Qualifications

  • Master’s or PhD in Computer Science, Machine Learning, Statistics, Applied Mathematics, or related field.
  • 7+ years of hands-on experience in machine learning, deep learning, or applied AI.
  • Proven experience with LLMs (e.g., GPT, LLaMA, Claude), Transformers, CNNs, RNNs , and generative models (e.g., GANs, VAEs).
  • Proficiency in Python, SQL, and ML libraries (TensorFlow, PyTorch, Hugging Face, etc.).
  • Familiarity with cloud platforms (AWS/GCP/Azure) and ML Ops tooling (Docker, Kubeflow, MLflow, Airflow).
  • Strong understanding of data structures, algorithms, and software design principles.
  • Excellent problem-solving skills, communication, and ability to translate business requirements into technical solutions.

Job Tags

Full time,

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