Associate Manager Data Science

This role involves working with our partners in different Therapeutic areas (eg Oncology, Vaccines, Pharma & Rare Disease, etc) and Domain areas (HCP Analytics, Patient Analytics, Segmentation & targeting, Market Access, etc) across the organization to help create scalable and production-grade analytics solutions, ranging from data visualization and reporting to advanced statistical and AI/ML models.

You will work in one of the three therapeutic areas of Brand Strategy and Performance Analytics - Oncology/Vaccines/Pharma & Rare Disease, where you will play a pivotal role in leveraging your statistical and machine learning expertise to address critical business challenges and derive insights to drive key decisions. Working alongside experienced data scientists and business analysts, you will have the opportunity to collaborate in translating business queries into analytical problems, employing your critical thinking, problem-solving, statistical, machine learning, and data visualization skills to deliver impactful solutions.

We are seeking candidates with prior experience in the healthcare analytics or consulting sectors, prior hands-on experience in Data Science (building end-to-end ML models). It is preferred that you have a good understanding of Physician and Patient-level data (PLD) from leading vendors such as IQVIA, Komodo, and Optum. Familiarity with HCP Analytics, PLD analytics, concepts like persistence, compliance, line of therapy, etc, or Segmentation & Targeting is highly desirable. You will be part of a dynamic team that collaborates with our partners across therapeutic areas. Furthermore, effective communication skills are crucial, as this role requires interfacing with executive and business stakeholders.

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:

Bachelor s degree with at least 1-3 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 (eg, claims, electronic health records) and data from common healthcare data vendors (IQVIA, Optum, Komodo, etc)
• Experience in HCP & Patient Level Data analytics (eg, 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

Required Skills: