Job Summary

Responsible for leading Axtria's Data Science practice for pharma commercial analytics, driving delivery excellence, client partnership, and hands-on solutioning across predictive modelling, Machine Learning, Deep Learning, Generative AI and Agentic AI. Acts as the senior-most Subject Matter Expert (SME) for Data Science solutions, setting technical direction, building reusable IP, and mentoring a large team of data scientists while owning delivery accountability for pharma clients.

Key Responsibilities –

- Delivery Leadership

- Own end-to-end delivery of data science engagements for pharma commercial clients, ensuring quality, timelines, and business impact.
- Manage senior client/onshore stakeholders (D/ED/VP/CxO level) to build trusted advisory relationships and drive account growth.
- Lead, mentor, and scale a large team of data scientists, managers, and leads; define team structure, career paths, and capability-building plans.
- Drive program governance – resource planning, risk management, quality assurance, and adherence to delivery SLAs/KPIs across multiple engagements.
- Partner with sales and account teams on pre-sales – solutioning, RFP/RFI responses, proposal development, effort estimation, and pricing.
- Identify opportunities for account mining, cross-sell/up-sell of analytics and AI/Gen AI offerings within existing pharma accounts.
- Collaborate with technology, platform, and consulting teams to align data science delivery with Axtria's broader product and consulting roadmap.
- Institutionalize best practices, delivery frameworks, and reusable accelerators to improve speed-to-value across engagements.

Key Responsibilities –

- Subject Matter Expertise (SME)

- Serve as the hands-on SME for predictive modelling, statistical modelling, Machine Learning, Deep Learning, Generative AI, and Agentic AI solutions.
- Architect and review solution design for complex analytics problems across patient journey analytics, HCP/payer/patient analytics, forecasting, and market mix modelling, recommendation engines.
- Provide technical oversight on model design, validation, performance benchmarking,



and responsible/explainable AI practices.
- Drive adoption of Generative AI and Agentic AI frameworks (e.g., LLM-based copilots, RAG pipelines, multi-agent orchestration) for pharma commercial use cases.
- Guide teams on MLOps/LLMOps practices – model deployment, monitoring, retraining, and governance at scale.
- Represent Axtria as a thought leader – author points of view (POVs), white papers, and present at internal/external forums and industry conferences.
- Evaluate emerging tools, platforms, and techniques in AI/ML/Gen AI and assess their applicability to pharma commercial analytics.
- Champion innovation – sponsor hackathons, incubate new solution frameworks, and contribute to Axtria's data science IP and accelerators.

Requirements

- 15+ years of overall experience in Data Science / Advanced Analytics, including at least 5+ years of Pharma commercial analytics experience.
- Demonstrated hands-on capability (not only oversight) in predictive modelling, Machine Learning, Deep Learning, Generative AI, and Agentic AI solutions.
- Proven experience managing large data science teams (30+ associates) across multiple concurrent client engagements.
- Solid track record of client relationship management with top pharmaceutical/life sciences companies.
- Experience contributing to pre-sales, proposal development, and account growth in a consulting/analytics services environment.
- Excellent executive communication, storytelling, and stakeholder management skills.
- Solid business acumen with the ability to translate analytics into commercial impact and ROI.

Qualifications

- Master's or Ph.D. in Statistics, Computer Science, Data Science, Economics, Mathematics, Operations Research, Engineering, or a related quantitative discipline.





Must-Have Skills

- Deep expertise in pharma commercial analytics –
- HCP, patient, and payer analytics; and pharma real-world data (APLD, EMR, prescription, claims, specialty pharmacy).
- Hands-on expertise in statistical modelling and AI/ML tools –
- Python, PySpark, SQL, Databricks, and cloud platforms (AWS/Azure/GCP).
- Strong command of ML algorithms –
- XGBoost, AdaBoost, Random Forest, K-means, clustering, segmentation, and lookalike modelling.
- Hands-on experience with Deep Learning frameworks –
- TensorFlow, PyTorch, Keras.
- Hands-on experience with Generative AI –
- LLMs (e.g., GPT, Claude, Llama), prompt engineering, RAG (Retrieval-Augmented Generation), and fine-tuning.
- Working knowledge of Agentic AI frameworks –
- LangChain, LangGraph, AutoGen, CrewAI, Semantic Kernel, or equivalent.
- Experience with MLOps/LLMOps practices –
- CI/CD for ML, model monitoring, and governance.
- Proven people leadership – managing, mentoring, and growing large, multi-level data science teams.

Nice-to-Have Skills

- Prior P&L; or account ownership within a consulting/analytics services organization.
- Publications, patents, or conference presentations in AI/ML/Gen AI.
- Experience building or scaling a Center of Excellence (CoE) for Data Science/AI within an organization.
- Relevant certifications in cloud, AI/ML, or Generative AI platforms.

What Axtria Provides

- Inclusive workplace encouraging diverse perspectives.
- Opportunities to shape and lead a transforming Data Science practice with global impact.
- Technical challenges at the intersection of pharma commercial strategy and cutting-edge AI/Gen AI.
- Self-development opportunities (Axtria Institute, certifications, knowledge sharing).
- Sponsored Tech Talks &
- Hackathons.
- Relocation opportunities across offices.
- Benefits: Health insurance, retirement, paid time off, flexible benefits, hybrid working.

Culture

- Equal opportunity employer valuing diversity and inclusiveness.
- 14 years of growth and recognition as a Great Place to Work.

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