Principal Data Scientist R
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Job Location:
Monthly Salary:
Posted on:
18 hours ago
Vacancies:
1 Vacancy
Job Summary
Principal Data Scientist
Primary Skills
- A/B Testing Clustering AWS Hypothesis Testing T-Test Z-Test Regression (Linear Logistic) Parameter Tuning Data Wrangling Exploratory Data Analysis Python/PySpark PCA Factor Analysis SAS/SPSS GitHub / Gitlab IBM Watson Feature Engineering Tree Aglorithms Grid Search SVM Tools(KubeFlow BentoML) Cross Validation Data Curiosity Design Thinking Data Literacy
Job requirements
- This role is explicitly focused on building agentic systems from scratch including the design and development of autonomous AI agents and enterprise copilots with hands-on experience in Microsoft 365 Copilot and Copilot Studio ecosystems as a core requirement. Core Responsibilities Agentic AI Architecture & Engineering: Build AI agents and multi-agent systems from scratch including agent orchestration autonomy design tool-use memory management and decision frameworks. Enterprise Copilot Development: Design build and scale enterprise copilots using Microsoft Copilot Studio and Microsoft 365 Copilot enabling intelligent task automation and knowledge workflows. Build AI agents & copilots on Microsoft Copilot Studio Develop automated workflows using Power Automate / Logic Apps Integrate AI agents with enterprise systems via APIs connectors and Azure services Implement RAG grounding semantic search using Azure OpenAI & Azure Cognitive Search Ensure security governance and responsible AI practices Collaborate with architects analysts and business teams 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.
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.
