Description

Advanced proficiency in AI innovation, specifically the application of agentic frameworks such as LangChain or LangGraph to solve autonomous operation challenges

Strong expertise in machine learning development using Python, PyTorch, and TensorFlow to construct models with high predictive power and statistical reliability.

Critical experience in LLM deployment strategies, including RAG optimization, fine-tuning, and performance inference across hybrid cloud environments

Deep technical understanding of MLOps lifecycle management within modern data platforms like Databricks or SageMaker to ensure scalable model delivery

Collaborative professional expertise in data storytelling, translating complex quantitative findings into strategic recommendations for C-suite stakeholders

Thorough knowledge of AI governance and responsible AI principles, including NIST AI RMF and TOGAF standards, to mitigate model risk and ensure ethical data application

Additional Qualifications

Familiarity with TM Forum ODA or telecom-specific data models

Exposure to on-premises AI infrastructure, including GPU cluster provisioning or Kubernetes platforms

Background in knowledge graphs or enterprise search optimization

Minimum Requirements

Minimum Education: Bachelor’s Degree in Computer Science, Data Science, Statistics, Electrical Engineering, or a related quantitative field

Minimum Experience: 5+ years of experience in data science

Required Technical Skills: Must have at least 2 years of experience with:

Python (Scikit-learn, PyTorch, or TensorFlow)

Databricks, Spark, or AWS (SageMaker/Bedrock)

SQL and cloud-native orchestration (dbt or Airflow)

Key Skills

Education

Bachelor's degree