Data Scientist

The core responsibilities for the job include the following:

Leadership and Delivery:

• Lead the architecture, development, deployment, and governance of enterprise AI/ML solutions.
• Lead complex data science projects end-to-end, delivering significant and measurable business impact.
• Define technical standards, reusable frameworks, and best practices for AI and machine learning development.
• Design and implement enterprise-wide data science frameworks, governance models, and best practices.
• Mentor and guide data scientists while promoting technical excellence.

Advanced Analytics and AI:

• Solve highly complex business problems using machine learning, statistical modeling, generative AI, and advanced analytics.
• Design and implement agentic workflows and multi-agent systems using frameworks such as LangGraph, CrewAI, AutoGen, and AWS AgentCore.
• Develop AI-powered solutions, including workflow copilots, intelligent automation agents, content generation systems, and code assistants.
• Drive AI governance, explainability, monitoring, validation, and responsible AI practices.

Stakeholder and Strategy:

• Partner with business leaders, clinical experts, statisticians, and technology teams to identify AI opportunities.
• Work closely with senior leadership to inform and influence strategic business decisions through data-driven insights.
• Translate complex analytics into actionable business recommendations.
• Define and execute the roadmap for AI, machine learning, and advanced analytics capabilities.

Technical Leadership:

• Design scalable AI architectures supporting large structured and unstructured datasets.
• Lead technology selection, solution design, model deployment, and continuous improvement initiatives.
• Evaluate emerging technologies and drive innovation across the organization.

Requirements:

• Master's or PhD in data science, computer science, statistics, artificial intelligence, mathematics, bioinformatics, or a related discipline.
• 8-12 years of experience in data science, AI, machine learning, or advanced analytics.
• Proven experience leading AI/ML initiatives from ideation through production deployment.
• Extensive experience leading complex data science projects from end-to-end and driving significant business impact.
• Proven track record of working closely with senior leadership to inform and influence high-level strategic business decisions.
• Demonstrated experience in designing and implementing enterprise-wide data science frameworks and best practices.
• Experience mentoring teams and providing technical leadership.
• Experience in pharmaceutical, life sciences, healthcare, or other regulated industries preferred.

AI, ML, and Generative AI:

• Expertise in machine learning, deep learning, NLP, predictive modeling, and statistical analysis.
• Deep knowledge of LLMs, prompt engineering, fine-tuning, agentic AI, and AI application architecture.
• Experience with LangChain, LangGraph, CrewAI, AutoGen, Semantic Kernel, MCP, and AWS AgentCore.

RAG and Knowledge Graphs:

• Hands-on experience with RAG, Agentic RAG, GraphRAG, Hybrid Search, Vector Databases, and Semantic Retrieval.
• Experience with Neo4j, knowledge graphs, ontologies, and enterprise search platforms.

Programming and Engineering:

• Expert proficiency in Python.
• Strong experience with R; SAS knowledge preferred.
• Knowledge of APIs, microservices, CI/CD, GitOps, testing frameworks, and software engineering best practices.

Cloud, MLOps, and LLMOps:

• Experience with AWS, Azure, or GCP.
• Strong understanding of MLOps/LLMOps, model governance, monitoring, automation, Docker, and Kubernetes.

Visualization and Communication:

• Experience with Tableau, Power BI, R Shiny, Plotly, or equivalent visualization tools.
• Strong storytelling, presentation, and executive communication skills.

Additional Qualifications:

• Strong leadership, mentoring, and stakeholder management capabilities.
• Ability to balance strategic thinking with hands-on execution.
• Excellent communication and influencing skills.
• Proven innovation mindset and cross-functional collaboration skills.
• Experience supporting GxP-compliant systems and regulatory requirements is highly desirable.