Assistant Manager-Data Science

Who you are:

• You understand the foundations of statistics and machine learning and can work in high performance computing/cloud environments, with experience/knowledge in aspects across statistical analysis, machine learning, model development, data engineering, data visualization, and data interpretation
• You are self-motivated, and have demonstrated abilities to think independently as a data scientist
• You structure your data science approach according to the necessary task, while appropriately applying the correct level of model complexity to the problem at hand
• You have an agile mindset of continuous learning and will focus on integrating enterprise value into team culture
• You are kind, collaborative, and capable of seeking and giving candid feedback that effectively contributes to a more seamless day-to-day execution of tasks

Key Responsibilities:

• Understand the business requirements and support the manager to translate those to analytical problem statements.
• Implement the solution steps through SQL/Python, appropriate ML techniques without rigorous handholding. 
• Follow technical requirements (Datasets, business rules, technical architecture) and industry best practices in every task.
• Collaborate with cross-functional teams to design and implement solutions that meet business requirements.
• Present the findings to US DS stakeholders in a clear and concise manner and address feedback.
• Adopt a continuous learning mindset, both technical and functional.
• Develop deep expertise in therapeutic area, with clear focus on commercial aspects.

Minimum Qualifications:

• Bachelors degree with at least 0-3 years industry experience (experience requirement can be waived off for exceptional candidates)
• Strong Python/R, SQL, Excel skills
• Strong foundations of statistics and machine learning

Preferred Qualifications:

• Advanced degree in STEM (MS, MBA, PhD)
• 1-3 years’ experience in healthcare analytics and consulting
• Familiarity with Physician and Patient-Level data (e.g., claims, electronic health records) and data from common healthcare data vendors (IQVIA, Optum, Komodo, etc.)
• Experience in HCP & Patient Level Data analytics (e.g., HCP Segmentation & targeting, Patient Cohorts, knowledge of Lines of Therapy, Persistency, Compliance, etc.)
• Proficiency in Data Science Concepts, Microsoft Excel and PowerPoint, and familiarity with Dataiku