Director - Data Science

Key Responsibilities

PL Ownership Strategic Growth

• Expand strategic partnerships, generate multi-million-dollar revenue streams, and deliver measurable outcomes
• Own and manage a portfolio PL with accountability for revenue growth, gross margins, and delivery excellence.
• Develop and convert pipeline opportunities by aligning client priorities with Axtrias data AI offerings. Lead consulting engagements to win new business opportunities in pharma and life sciences.
• Influence account strategy, pricing models, investment cases, and strategic alliances.

Client Advisory Large Scale Delivery

• Oversee solution delivery of large-scale data and AI programs ensuring scientific rigor, innovation velocity, and commercial impact.
• Drive adoption of cloud-native architectures, modern data platforms, and AI/Agentic AI solutions.
• Ensure compliance with industry standards, data governance, and security protocols.

Team Leadership Capability Building

• Build and mentor high-performing teams across data engineering, analytics, and AI disciplines.
• Foster a culture of innovation, collaboration, and continuous learning.
• Foster a high-performance culture anchored in continuous learning, ethical AI, and measurable impact.

IP, Innovation and Thought Leadership

• Lead the development of next-gen agentic architectures that support autonomous decisioning, adaptive learning loops, and personalized interventions.
• Contribute to the firms IP portfolio through thought leadership, open-source tooling, and platform accelerators.
• Publish whitepapers, blogs, and POVs on emerging trends in AI, data management, and pharma analytics.

Required Skills Experience

• 12+ years in data management, AI/ML consulting, or digital transformation, with a minimum of 5 years focused on life sciences or healthcare.
• Bachelors degree a must w/ masters or PhD in Computer Science or related quantitative field.
• Proven expertise in Python, R, TensorFlow, Keras, NLP, deep learning, and big data.
• Hands-on experience with cloud platforms (AWS/Azure), ML pipelines, automation, and deployment.
• Hands-on knowledge of AI/ML frameworks, Agentic AI, and generative AI technologies. Strong grasp of data management, governance, and advanced analytics.
• Led complex, enterprise-scale AI/ML transformations in commercial pharma, HEOR, medical affairs, and patient analytics.
• Strong consultative and client-facing experience with a commercial mindset.
• Experience in RFP development, solution selling, and delivering data AI applications in life sciences.
• Knowledge of digital automation tools (e.g., low/no-code platforms, APIs, DevOps) a plus.
• Patents or publications in AI/ML a strong plus.