Principal Data Scientist R
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Job Location:
Monthly Salary:
Posted on:
16 hours ago
Vacancies:
1 Vacancy
Job Summary
Principal Data Scientist
Primary Skills
---Principal Data Scientist Agentic AI
---Lead Data Scientist LangChain OR LangGraph
---LLM fine-tuning production
---multi-agent OR autonomous agents LLM
---RAG pipeline
---GenAI leadership MLOps
---LLM fine-tuning production
---multi-agent OR autonomous agents LLM
---RAG pipeline
---GenAI leadership MLOps
Specialization
1. Agentic AI (multi-agent workflows autonomous agents tool-using agents)
2. LLMs (fine-tuning prompt engineering RAG pipelines production deployment)
3. LangChain / LangGraph / LlamaIndex / CrewAI / AutoGen
4. MLOps / LLMOps (model monitoring CI/CD versioning)
2. LLMs (fine-tuning prompt engineering RAG pipelines production deployment)
3. LangChain / LangGraph / LlamaIndex / CrewAI / AutoGen
4. MLOps / LLMOps (model monitoring CI/CD versioning)
Job requirements
The Principal Data Scientist will play a critical role in translating complex business problems into scalable AI-driven solutions. This role demands strong leadership deep expertise in Agentic AI Large Language Models (LLMs) and advanced analytics along with the ability to influence senior stakeholders and drive measurable business outcomes.
Core Responsibilities
- Problem Formulation: Translate business objectives into well-defined data science ML and Agentic AI problems; validate OKRs using robust statistical and experimental measures.
- Agentic AI & LLM Solutions: Design build deploy and optimize Agentic AI systems (multi-agent workflows task orchestration autonomous decision-making) using LLMs for real-world enterprise use cases.
- LLM Development & Deployment: Fine-tune prompt-engineer evaluate and productionize LLMs (open-source or proprietary) for use cases such as copilots RAG pipelines conversational AI and intelligent automation.
- Data Wrangling & Feature Engineering: Handle structured and unstructured data at scale including text documents and conversational data for LLM-powered solutions.
- Insight Generation & Data Storytelling: Convert complex analytical outputs and AI model results into clear compelling narratives for business and executive audiences.
- Technical Decision-Making: Make informed trade-offs on model complexity iteration depth experimentation cycles and time-to-value.
- Design Thinking & Innovation: Apply design thinking principles to build user-centric AI products and data solutions.
- Mentorship & Leadership: Coach senior data scientists review architectures and establish best practices across data science ML and GenAI initiatives.
Key Qualifications Technical Expertise
- Principal Data Scientist with strong hands-on experience in LLMs and Agentic AI.
- Proven experience in deploying fine-tuning and operationalizing LLMs in at least one real-world production-grade project.
- Hands-on expertise in Agentic AI frameworks and patterns such as multi-agent systems autonomous workflows tool-using agents and human-in-the-loop architectures.
- 1418 years of experience in Data Science Machine Learning Advanced Analytics or AI with at least 5 years in a technical leadership role.
- Proficiency in Python (mandatory); exposure to R or Scala is a plus.
- Strong foundation in machine learning deep learning NLP and statistical modeling.
- Experience with LLM ecosystems and frameworks (e.g. LangChain LangGraph LlamaIndex CrewAI AutoGen Hugging Face).
- Expertise in cloud platforms (AWS Azure or GCP) big data technologies and MLOps / LLMOps (model monitoring versioning CI/CD cost optimization).
- Hands-on experience with TensorFlow PyTorch Scikit-learn and related ML frameworks.
- Strong understanding of Responsible AI model governance explainability and risk management especially for GenAI solutions.
Leadership & Communication
- Proven ability to lead inspire and scale high-performing data science and AI teams.
- Exceptional communication and storytelling skills with the ability to influence senior leadership and business stakeholders.
- Demonstrated experience mentoring coaching and upskilling data scientists and ML engineers.
- Strong business acumen with the ability to quickly understand new domains and apply AI effectively.
Education
- Masters or Ph.D. in Data Science Computer Science Statistics Mathematics or a related field.
Critical Leadership Qualities
- Customer Advocacy: Drives customer success by anticipating both stated and unstated business needs using AI-led market-leading solutions.
- Owners Mindset: Demonstrates deep ownership of outcomes and makes decisions aligned with Brillios long-term success.
- Innovation Ethos: Embraces ambiguity experiments relentlessly and challenges the status quoespecially in GenAI and Agentic AI adoption.
- Execution with Pace: Delivers high-quality production-ready AI solutions in fast-changing environments.
- Big Picture Thinking: Aligns AI data and business strategy to create shared success and ambitious growth targets.
- Winning Through Teams: Builds a collaborative culture that empowers teams to excel and innovate together.
We may use artificial intelligence (AI) tools to support parts of the hiring process such as reviewing applications analyzing resumes or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed please contact us.
Required Experience:
Staff IC
Key Skills
- Machine Learning
- Python
- Data Science
- AI
- R
- Research Experience
- Sensors
- Drug Discovery
- Research & Development
- Natural Language Processing
- Data Analysis Skills
- Toxicology Experience
About Company
Brillio is a global leader in Enterprise Digital Transformation Solutions, providing strategic consulting services and solutions using emerging technologies.
