Senior Manager - Patient Analytics
Noida, Uttar Pradesh, India · Full Time
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- Experience
- 8–11 yrs
- Salary
- —
- Openings
- 1
- Posted
- 4 hours ago
- Work mode
- In office
- Education
- B.Tech / B.E. in Any Specialization
- Eligibility
- Candidates holding a Bachelor of Technology or Bachelor of Engineering degree in any specialization are eligible to apply.
- Resume
- Required to apply
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Job description
About Axtria
Axtria India Private Limited delivers cutting-edge cloud-based software and advanced data analytics solutions to the life sciences sector. Supporting pharmaceutical, medical device, and diagnostics companies, Axtria helps transform product commercialization processes while enhancing healthcare outcomes globally.
Position Summary
The Senior Manager role focuses on leading data science initiatives in predictive analytics, including clustering, segmentation, and lookalike modeling, centered around analyzing anonymized patient-level data to deepen patient journey insights. This position demands thought leadership in patient and predictive analytics and guides teams serving pharmaceutical clients.
Key Responsibilities
- Oversee interactions with clients and onshore stakeholders to ensure project success.
- Partner with project managers to define analytic algorithms, decompose complex problems, and execute analyses.
- Produce high-quality analytic solutions and comprehensive client-ready reports.
- Lead project scoping, design effective solutions, implement, and present findings clearly.
- Support enhancement of internal Axtria analytics tools and capabilities.
- Engage in hackathons, innovatively design solutions, and automate relevant processes.
- Maintain effective communication with clients and cross-functional teams onshore.
Candidate Requirements
- 8 to 11 years of experience in the pharmaceutical or life sciences industry.
- Proficiency in data science, machine learning algorithms, including predictive analytics, clustering, segmentation, and lookalike modeling.
- Experience in advanced analytics related to patient journey insights, such as therapy lines, switch analysis, adherence, and patient identification.
- Strong expertise in pharmaceutical commercial analytics involving healthcare professionals, payers, and patient datasets.
- Excellent logical reasoning, analytical structuring, and problem-solving skills.
- Ability to create compelling data visualizations, storytelling, and comprehensive reporting.
Educational and Technical Qualifications
- Bachelor's or Master's degree in Statistics, Economics, Mathematics, Operations Research, Engineering, Technology, Pharmacy, or Management.
- In-depth knowledge of pharmaceutical real-world data sources including APLD, EMR, prescriptions, and specialty pharmacy data.
- Hands-on experience with statistical modeling and AI/ML frameworks and tools such as Python, PySpark, and Databricks.
- Familiarity with machine learning algorithms like XGBoost, AdaBoost, Random Forest, and K-means clustering.
- Preferably, experience with deep learning technologies including Keras and TensorFlow.