Architect-GenAI+Pharma

Job Title : Architect-GenAI+Pharma

Experience: 8-12 yrs.

Location : Chennai, Hyderabad, Bangalore, Pune, Noida, Gurgaon, Delhi

Who we are

Tiger Analytics is a global leader in AI and analytics, helping Fortune 1000 companies solve their toughest challenges. We offer full-stack AI and analytics services & solutions to empower businesses to achieve real outcomes and value at scale. We are on a mission to push the boundaries of what AI and analytics can do to help enterprises navigate uncertainty and move forward decisively. Our purpose is to provide certainty to shape a better tomorrow.

Our team of 4000+ technologists and consultants are based in the US, Canada, the UK, India, Singapore and Australia, working closely with clients across CPG, Retail, Insurance, BFS, Manufacturing, Life Sciences, and Healthcare. Many of our team leaders rank in Top 10 and 40 Under 40 lists, exemplifying our dedication to innovation and excellence.

We are a Great Place to Work-Certified™ (2022-24), recognized by analyst firms such as Forrester, Gartner, HFS, Everest, ISG and others. We have been ranked among the ‘Best’ and ‘Fastest Growing’ analytics firms lists by Inc., Financial Times, Economic Times and Analytics India Magazine.

Curious about the role? What your typical day would look like?

As a Architect– GenAI + Pharma, you will be responsible for leading end-to-end Data Science, Machine Learning, and GenAI solutions for Pharma and Life Sciences commercial analytics engagements. You will work closely with onshore clients and cross-functional teams to translate complex business problems into scalable AI solutions across commercial analytics, forecasting, segmentation, targeting, patient/HCP analytics, and GenAI-powered applications.

• Data Science & AI Leadership: Lead end-to-end delivery of Data Science, Machine Learning, and GenAI workstreams for Pharma and Life Sciences engagements.
• Pharma Commercial Analytics: Drive analytical solutions across segmentation & targeting, omnichannel analytics, forecasting, alignment, goal setting, patient journey analytics, patient finding, and marketing mix modeling (MMM).
• GenAI Solution Development: Design and develop enterprise GenAI/LLM solutions for Pharma and Life Sciences use cases, including intelligent assistants, conversational AI, knowledge extraction, summarization, and decision-support applications.
• LLM & RAG Architecture: Design and implement RAG-based solutions, leveraging LLMs, embeddings, vector databases, prompt engineering, retrieval mechanisms, and structured/unstructured enterprise data.
• Agentic AI: Develop and guide the implementation of AI agents and agentic workflows for automating complex analytical and business processes.
• Model Development: Guide Data Scientists and ML Engineers on statistical modeling, machine learning, forecasting, experimentation, model validation, and productionization.
• Pharma Data Analytics: Work with commercial Pharma data including Rx data, claims data, HCP/patient datasets, CRM/call activity data, and primary/secondary market data.
• Technical Quality: Own technical quality through code reviews, model and LLM evaluation, performance optimization, documentation, reproducibility, and responsible AI practices.
• AI Productization: Partner with engineering teams to operationalize Data Science and GenAI solutions through APIs, dashboards, analytical products, platforms, and enterprise applications.
• Cloud & Data Platforms: Leverage modern cloud and data platforms to build scalable AI and analytics solutions using technologies such as Azure/AWS/GCP, Databricks, and Snowflake.
• Client & Stakeholder Management: Work directly with onshore/client stakeholders to understand business problems, communicate analytical insights, present solutions, and drive successful delivery.
• Solution Engineering & Consulting: Contribute to solutioning, proposals, and new business opportunities involving Pharma commercial analytics, Data Science, AI, and GenAI.
• Team Leadership & Mentoring: Lead, mentor, and develop Data Scientists, ML Engineers, and GenAI talent while fostering strong technical and analytical capabilities within the team.

What do we expect?

• Pharma/Life Sciences Experience: 8-12 years of experience in Data Science, Advanced Analytics, Machine Learning, or AI, with meaningful hands-on experience in Pharma/Life Sciences commercial analytics.
• GenAI & LLM Expertise: Strong hands-on experience developing Generative AI/LLM solutions for enterprise use cases. Experience with RAG, prompt engineering, embeddings, vector databases, LLM evaluation, and AI agents is highly desirable.
• Pharma Commercial Analytics: Proven experience across Pharma use cases such as segmentation & targeting, omnichannel analytics, forecasting, MMM, patient finding, patient journey analytics, alignment, and goal setting.
• Pharma Data Expertise: Strong understanding of Pharma commercial data sources including Rx data such as IQVIA/Symphony, medical/pharmacy claims, HCP and patient-level datasets, CRM/call activity data, and primary/secondary market data.
• Python & SQL: Strong proficiency in Python and SQL, with hands-on experience in data analysis, feature engineering, statistical modeling, and machine learning.
• Machine Learning & Statistical Modeling: Strong understanding of regression, classification, clustering, time-series forecasting, predictive modeling, and other standard ML/statistical techniques.
• RAG & Agentic AI: Experience designing and implementing RAG pipelines and/or agentic AI solutions, including retrieval, context management, tool integration, and LLM orchestration.
• AI & Data Integration: Experience working with structured and unstructured enterprise data and integrating Data Science/GenAI solutions with modern data platforms and applications.
• Cloud & Modern Data Stack: Experience with Azure/AWS/GCP and modern data platforms such as Databricks and Snowflake is preferred.
• Pharma Data Privacy & Compliance: Familiarity with Pharma-specific data privacy and compliance requirements such as HIPAA, PHI handling, data security, and responsible AI is preferred.
• Client & Stakeholder Management: Strong experience working directly with onshore/client stakeholders, with excellent communication, presentation, consulting, and stakeholder management skills.
• Leadership & Mentoring: Demonstrated ability to lead technical teams, review solutions, mentor talent, and drive high-quality delivery.
• Solutioning & Consulting: Ability to translate complex Pharma business problems into scalable Data Science, AI, and GenAI solutions and contribute to proposals and solutioning discussions.
• Productionization: Experience deploying and maintaining ML/AI/GenAI solutions in enterprise environments, with a strong focus on scalability, performance, security, reliability, and maintainability.

You are important to us, let’s stay connected!

Every individual comes with a different set of skills and qualities so even if you don’t tick all the boxes for the role today, we urge you to apply as there might be a suitable/unique role for you tomorrow. We are an equal opportunity employer. Our diverse and inclusive culture and values guide us to listen, trust, respect, and encourage people to grow the way they desire.

Note: The designation will be commensurate with expertise and experience. Compensation packages are among the best in the industry.

Mandatory Skills

Pharma,Life Sciences,Retrieval Augmented Generation,Python,SQL,Agentic Ai,Large Language Model

Role

Key Responsibilities

• Lead end-to-end delivery of Data Science and GenAI workstreams for pharma commercial analytics engagements, spanning use cases such as segmentation & targeting, alignment, goal setting, forecasting, omnichannel analytics, and GenAI-enabled solutions.
• Translate business problems from onshore/client stakeholders into data science, machine learning, and GenAI solution approaches, model designs, and delivery plans.
• Drive the design and development of GenAI/LLM solutions for pharma and life sciences use cases, including RAG, conversational AI, intelligent assistants, summarization, knowledge extraction, and other enterprise GenAI applications.
• Guide a team of data scientists, ML engineers, and GenAI engineers on solution development, validation, optimization, and productionization.
• Own technical quality across ML and GenAI solutions, including code reviews, model/LLM performance, evaluation frameworks, documentation, reproducibility, and responsible AI practices.
• Partner with engineering teams to operationalize models and GenAI solutions into analytical products, dashboards, APIs, platforms, and enterprise applications.
• Function as a bridge between offshore delivery teams and onshore account/client leads, ensuring timely, high-quality delivery and effective stakeholder communication.
• Contribute to solutioning, architecture, and proposal development for new Pharma/Life Sciences opportunities, particularly involving Data Science, GenAI, and advanced analytics.
• Mentor and grow Data Science and GenAI talent within the pod.

Education Qualification

B.E/B.Tech

Experience

8 to 12 years