Manager - Data Analytics (Pharma)
Вакансия из Hirify Global, списка международных tech-компанийДля мэтча и отклика нужен Plus
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
TL;DR
Manager - Data Analytics (Pharma): Leading complex data analytics programs and decisioning systems within the pharmaceutical domain with an accent on Next Best Action (NBA) frameworks and predictive modeling. Focus on building scalable ML pipelines, managing stakeholder expectations, and driving outcomes through advanced data engineering and MLOps practices.
Company
is a technology-led healthcare solutions provider specializing in commercial, medical, and clinical operations for the life sciences industry.
What you will do
- Lead and deliver complex data analytics programs for commercial, sales, and marketing pharma domains.
- Design and implement Next Best Action (NBA) and decisioning systems to drive business outcomes.
- Develop predictive models including classification, clustering, and time series forecasting using Python and PySpark.
- Oversee MLOps workflows including model deployment, monitoring, and CI/CD pipelines on AWS and Databricks.
- Manage stakeholder and client relationships, ensuring project accountability and high-quality delivery.
- Mentor and lead teams, fostering an ownership mindset and technical excellence.
Requirements
- 12+ years of total experience with at least 5+ years in a Project Lead role.
- Strong Pharma industry experience in commercial, sales, marketing, or medical analytics.
- Advanced proficiency in Python, SQL, and PySpark.
- Proven expertise in predictive modeling and model explainability (SHAP/LIME).
- Experience with cloud platforms (AWS) and data platforms (Databricks).
- Strong communication and problem-solving skills with a focus on stakeholder management.
Nice to have
- Experience with GenAI, LLMs, and prompt engineering.
- Knowledge of agent-based systems and vector databases.
- Proficiency in BI tools like Power BI or Tableau.
Culture & Benefits
- Opportunity to work on high-impact healthcare and life sciences projects.
- Collaborative environment focused on innovation and technical growth.
- Exposure to cutting-edge AI/ML and MLOps technologies.
- Emphasis on professional development and leadership accountability.
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