Axtria
Project Lead/Manager/Senior Manager - Patient Predictive Analytics
Skills
1 month ago
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Important information
Contract type:
Permanent
Location:
Bengaluru, Karnataka, India
Work mode:
Onsite
Published on:
15 September 2026
What they need
Role & responsibilities
Responsible for data science solutioning (predictive analytics, clustering, segmentation, lookalike modelling), augmenting patient journey analysis and working with anonymized patient-level data. Acts as an expert in Patient and Predictive Analytics, guiding and leading teams supporting pharma clients.
Key Responsibilities :
Manage client/onshore stakeholders to ensure successful delivery.
Collaborate with project managers to define algorithms, break down problems, and run analyses.
Deliver high-quality analytics solutions/reports in client-ready formats.
Scope projects, design solutions, execute, and communicate findings.
Contribute to Axtria tools and capabilities.
Participate in hackathons, solution design, and process automation.
Communicate effectively with clients and onshore teams.
Requirements :
-3- 9 years of experience in Pharmaceutical/Life Sciences domain.
Expertise in Data Science/ML algorithms, predictive analytics, clustering, segmentation, lookalike modelling, statistical models
Experience with advanced analytics across patient journey (line of therapy, switch analysis, segmentation, adherence, patient identification, etc.).
Expertise in commercial pharmaceutical analytics (HCP, payer, patient analytics).
Strong logical reasoning, structuring of analysis, problem-solving.
Skills in data visualization, story-telling and reporting.
Qualifications :
Bachelors/Masters in Statistics, Economics, Mathematics, Operations Research, Engineering, Technology, Pharmacy, Management
Must-Have Skills :
Expertise in pharma real-world data (APLD, EMR, prescription, specialty pharmacy).
Experience in statistical modelling and AI/ML tools (Python, PySpark, Databricks).
Algorithms - XGBoost, AdaBoost, Random Forest, K-means, etc.
Nice-to-Have Skills :
- Experience in Deep Learning (Python, PySpark, Keras, TensorFlow).
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