RGM – Data Scientist

Responsibilities

RESPONSIBILITIES:

• Invent, research, envision, design, solution and deliver AI/ ML applications at scale delivering measurable value
• Build end-to-end AI/ ML solutions: Develop, refine, implement, customize and deploy state-of-the-art Machine Learning algorithms and systems, and AI models
• Designing, developing, and researching Machine Learning systems, models, and schemas through data science and data analytics prototypes.
• Continuous learning – Certifications.
• Incubation mindset – Research oriented, ability to deliver quick POC’s, and come up with ideas.
• Communication and Documentation – Ability to share knowledge, conduct presentations and sessions, talk to clients and stakeholders, write good-quality technical documentation.
• Problem Solving – Technical depth in solving real-world problems with appreciation of business imperatives.

Additional Responsibilities

SKILLS – GOOD TO HAVE:

• Linux shell-scripting
• Multilingual NLP

SOFT SKILLS:

• Good communication
• Ability to work in a team as well as independently deliver modules
• Team player

LEADERSHIP SKILLS:

• People Leadership: Able to lead and mentor a team of ~10-15 people
• Thought Leadership: Having papers published in renowned journals, presentations in conferences, patent-filing preferred

Technical and Professional Requirements

SKILLS – MUST HAVE:

• Design, build, and deploy Hyperscalers-based (Azure, AWS, GCP or Databricks) ML models, including large-scale data processing, computationally intensive statistical modeling, and advanced analytics – Expert
• Implementation of Generative AI models for business solutions and experience on Azure Open AI, AWS Bedrock or Vertex AI or open-source models – Expert
• Python programming with robust code – Expert
• Developing a framework or generic pipeline to retrieve, optimize, and deploy Open-Source Models – Expert
• Explore and design a reference architecture for developing virtual assistants using foundation models – Expert
• Familiarity with deep learning, machine learning and frameworks (like Keras, TensorFlow or PyTorch etc.), HuggingFace Transformers and libraries (like scikit-learn, spacy, gensim, CoreNLP etc.) – Working knowledge
• Understanding of LLMs and Gen AI especially as applied to text and image analysis and training – Working knowledge
• Experienced in fine-tuning of LLM models, implementation of AI Guardrails and Responsible AI Framework (explainability, bias detection, hallucination control) – Working knowledge
• Experienced in implementing LangChain Frameworks – Working knowledge
• Linux, HTTP/ REST – Working knowledge
• Cloud Technologies – At least one of GCP, AWS, Azure
• JIRA, Conflence – Working knowledge

Preferred Skills

• Databricks Machine Learning
• Artificial Intelligence – BASIC

Educational Requirements

Diploma of Applied Science,PhD of Computer Science,PhD of Mathematics,Bachelor of Engineering