AI and data platform for life sciences commercial operations
Axtria is a data and AI specialist serving the life sciences industry, with a stack anchored on Databricks, Python, and cloud analytics (AWS, Azure, Redshift, Tableau). The company is actively adopting Delta Lake, Lakehouse architecture, and generative AI (Langchain, GPT) while replacing Apache Airflow — a pattern signaling a shift from orchestrated batch pipelines toward real-time, AI-driven insights. Hiring is heavily weighted toward data roles (129 open positions) relative to engineering (20) and sales (30), reflecting an organization built around analytics delivery rather than software product development.
Notable leadership hires: AI & Data Science Lead, Project Lead, Director Consulting, Account Director, GenAI Application Lead
Axtria develops cloud software and data analytics solutions for pharmaceutical, insurance, and life sciences companies. The platform helps clients move from raw data through analytics to actionable commercial insights, spanning sales planning, incentive compensation management, and market analytics. Operating across 75+ countries with 1,001–5,000 employees, the company combines consulting, data integration (Informatica, Matillion, DataStage), and BI tooling (Tableau, Qlik, Power BI) to support the full product commercialization cycle. Current work centers on modernizing data platforms via Databricks and lakehouse architecture, scaling AI/ML delivery capabilities, and moving proof-of-concept projects into production—areas where compliance, data governance, and production readiness remain ongoing challenges.
Axtria uses Python, R, TensorFlow, Keras, AWS, Azure, Databricks, PySpark, Informatica, Matillion, Redshift, Tableau, Qlik, Power BI, and Salesforce. The company is actively adopting Delta Lake, Lakehouse, Dataiku, Langchain, and GPT while moving away from Apache Airflow.
Current initiatives include delta lakehouse implementation, agentic architecture development, data modernization, scalable data pipelines on Databricks, GenAI applications, and transitioning proof-of-concept solutions to production environments.
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