
Advisor, Data Science (I7)
- Bangalore, Karnataka
- Permanent
- Full-time
As a Data Science Advisor, you will be responsible for contributing to business strategy and influence decision making based on information gained from deep dive analysis. You will produce actionable and compelling recommendations by interpreting insights from complex data sets. You will design processes to consolidate and examine unstructured data to generate actionable insights. You will also partner with business leaders, engineers and industry experts to construct predictive models, algorithms and probability engines.You will:
- Play a key role in designing and implementing intelligent solutions using Generative AI, Large Language Models (LLMs), and Machine Learning and work closely with senior architects and cross-functional teams to bring AI-driven innovations to life, particularly in the domain of technical support services and enterprise automation.
- Contribute to the design and development of GenAI and LLM-based solutions for enterprise-scale use cases and collaborate with senior data scientists and engineers to build, fine-tune, and deploy NLP and deep learning models.
- Assist in the integration of AI models into existing systems and workflows, ensuring performance and scalability and participate in data preparation, feature engineering, and model evaluation for various AI/ML projects.
- Stay updated on the latest trends in AI/ML, LLMs, and MLOps, and bring innovative ideas to the team and support the monitoring and optimization of deployed models using MLOps tools and best practices.
Every Dell Technologies team member brings something unique to the table. Here’s what we are looking for with this role:Essential Requirements
- Bachelor’s or Master’s degree in Computer Science, Data Science, AI/ML, or a related field.
- 4–8 years of hands-on experience in data science, machine learning, or AI solution development.
- Proficiency in Python, with experience in libraries such as TensorFlow, PyTorch, or Hugging Face Transformer and Familiarity with LLMs, NLP techniques, and Generative AI frameworks.
- Experience working with cloud platforms (AWS, Azure, or GCP) and containerization tools like Docker.
- Strong analytical, problem-solving, and communication skills.
- Exposure to MLOps tools (e.g., MLflow, Kubeflow, SageMaker) and model lifecycle management and understanding of data engineering concepts and tools like Spark, Kafka, or Airflow.
- Experience with REST APIs, microservices, and integrating ML models into production environments and knowledge of DevOps practices, CI/CD pipelines, and Kubernetes is a plus.
- Ability to work in agile teams and contribute to multiple projects simultaneously.