Director - Data Science

Job description

**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.