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Tiger Analytics - Architect/Senior Architect - Data & AI

Tiger Analytics
8 - 12 Years
Multiple Locations

Posted on: 08/10/2026

Job Description

Architect/Senior Architect - Data and AI

Who we are :

Tiger Analytics is a global leader in AI and analytics, helping Fortune 1000 companies solve their toughest challenges. We offer fullstack AI and analytics services and solutions to empower businesses to achieve real outcomes and value at scale.

What your typical day would look like :

Key Responsibilities :

- Lead end-to-end delivery of data science workstreams for pharma commercial analytics engagements, spanning use cases including but not limited to segmentation and targeting, alignment, goal setting, forecasting.

- Translate business problems from onshore/client stakeholders into technical approaches, model designs, and delivery plans.

- Guide a team of data scientists and ML engineers on model development, validation, and productionization.

- Own technical quality code review, model performance, documentation, reproducibility.

- Partner with engineering teams to operationalize models into analytical products (dashboards, APIs, platforms).

- Function as a bridge between offshore delivery teams and onshore account leads, ensuring timely, high-quality outputs.

- Contribute to proposal and solutioning efforts for new pharma opportunities as needed.

- Mentor and grow data science talent within the pod.

What we expect :

- 8 - 12 years of experience in data science / advanced analytics, with meaningful exposure to pharma or life sciences commercial analytics.

- Hands-on experience across pharma commercial use cases such as segmentation and targeting, omnichannel analytics, marketing mix modeling (MMM), patient finding, forecasting, patient journey analytics.

- Working knowledge of pharma commercial data sources such as prescription (Rx) data (e.g. IQVIA, Symphony), medical/pharmacy claims data, HCP and patient-level datasets, CRM/call activity data, primary and secondary market data.

- Strong skills in Python, SQL, and standard ML/statistical modeling techniques (regression, time-series, classification, clustering).

- Comfortable working directly with onshore stakeholders effective communication and stakeholder management skills.

- Experience with cloud platforms (Azure/AWS/GCP) and modern data stacks (Snowflake, Databricks) is a plus.

- Familiarity with pharma-specific data privacy and compliance considerations (e.g. HIPAA, PHI handling) is a plus.

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

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