
Data Insights Strategist
1 week ago
Job Summary:
The Data Insights Leader plays a pivotal role in driving business growth through data-driven insights and strategic decision-making. This senior leadership position requires a strong technical background, with a minimum of 8+ years of experience in ML/DL development.
The ideal candidate will have hands-on experience with production projects, leveraging skills in Python, deep learning frameworks (Tensor Flow, Keras, or PyTorch), NLP libraries (NLTK, SpaCy, and Huggingface transformers), and Generative AI models. Proficiency in cloud platforms (Azure or AWS), API endpoints (FastAPI), and MLOps tools (Dagster, Airflow, MLFlow) is also essential.
This role demands strong problem-solving skills, the ability to work independently and collaboratively, and effective communication skills to present complex technical concepts to non-technical stakeholders.
Key Responsibilities:
- Develop and implement advanced machine learning models for business growth
- Leverage NLP and deep learning techniques to drive data insights and inform strategic decisions
- Collaborate with cross-functional teams to integrate analytics into business processes
- Maintain and improve existing analytics infrastructure, including cloud platforms and MLOps tools
- Communicate complex technical concepts to both technical and non-technical stakeholders
Requirements:
- 8+ years of relevant experience in ML/DL development
- Hands-on experience with production projects, focusing on technical aspects
- Strong understanding of NLP, deep learning, and neural networks
- Proficiency in Python and at least one deep learning framework (Tensor Flow, Keras, or PyTorch)
- Familiarity with NLP libraries (NLTK, SpaCy, and Huggingface transformers)
- Working knowledge of Generative AI models and their architectures
- Familiarity with at least one cloud platform (Azure or AWS)
- Proficiency in exposing solutions as API endpoints using ASGI frameworks (FastAPI)
- Experience with development tools (Git and version control)
- Familiarity with MLOps tools (Dagster, Airflow, MLFlow) for building orchestration pipelines
- Strong problem-solving skills and ability to work independently and collaboratively
- Effective communication skills to present complex technical concepts to non-technical stakeholders
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