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EVERSANA India Pvt. Ltd

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Manager-Data Science

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Summary

Manager-level patient analytics role in Bengaluru: lead real-world evidence (RWE) projects for pharmaceutical clients, drafting research proposals and statistical analysis plans, guiding a team, and building models and applications in SQL, Python, and R on healthcare claims data, with client-facing visualizations and delivery under timelines.

Job Description
Job Overview: Manager - Patient Analytics
We are looking for an experienced professional to lead patient analytics projects, working closely with pharmaceutical clients to deliver robust analytical solutions. The ideal candidate should have strong technical expertise, hands-on experience with patient-level data, and the ability to engage directly with clients while guiding a team.
Key Responsibilities
- Act as a subject matter expert to determine scientific and methodological aspects of RWE projects.
- Independently draft and edit high quality research proposals and statistical analysis plans.
- Guide team members with components of RWE analysis, such as, cohort creation, target/control creation, comorbidity analysis, adverse reactions, line of therapy, cost analysis, provider and payer analysis, KOL segmentation and targeting etc., based on clinical knowledge of disease area.
- Develop and apply data mining, statistical, machine learning techniques and models to extract analytic insights from healthcare and non-healthcare data sets.
- Develop software solutions and applications using SQL, Python, and/or R.
- Responsible for review, generation, and delivery of analytic products in support of project work, RFP responses and other business needs.
- Support the development of visualizations and presentations for client deliverables.
- Interface with EVERSANA analysts, data scientists, clinicians, program managers and with EVERSANA customers.
- Responsible for the development and delivery of projects within defined timelines. - Respond to additional ad-hoc analysis requests.
Job Requirements
- 7-12 years of experience in data analytics and modeling, preferably around healthcare claims data and commercial analytics in the life science industry.
- Practical knowledge of statistics, statistical inference, and machine learning algorithms (deep learning, LSTM, SVM, CNN, GAN, and reinforcement learning)
- Hands-on experience and proficiency in SQL, Python, (pandas, scikit-learn, numpy, scipy) R, visualization tools, and software development within a Linux environment
- Deep commercial awareness of the healthcare, health technology and pharmaceutical industry, gained through experience
- High level of knowledge and analytic experience with real world data sources (e.g., EHR/EMR data, RWD, healthcare prescription / claims databases) as well as comprehensive understanding of the RWD supply chain and reimbursement policies
- Expertise in healthcare industry terminology and coding (e.g. NDC11, ICD9/ ICD10, HCPCS, CPT, LOINC)
- Works independently and is a self-starter
- MS PowerPoint presentation development skills
- Client interface and presentation skills
- Ability to lead by example
- Strong organizational skills, including ability to manage multiple deliverables across multiple projects
- Significant consideration will be given to prior publications, independent software projects completed, and non-proprietary code authored by the candidate.
Qualifications
- Bachelor s degree (preferably in Engineering) from a reputed institution, with strong experience in life sciences and claims data analytics.
- Degree in any of the following majors: Epidemiology, Biostatistics, Bioinformatics, Statistics, or similar
- Master s degree (MBA) from a recognized institution is preferred Expectations
- Hours (40 Hours per week, 5 days of the week) - Shift Timing: 11:30 AM to 8:30 PM IST (fluid based on requirement).

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.

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