Knowledge Foundry - Data Analytics Specialist - Clinical Datasets (3-5 yrs)

We are seeking a Patient-Level Data Analytics Specialist with 3-5 years of experience in analyzing US patient-level claims data.

The ideal candidate will have strong expertise in real-world pharma datasets and hands-on experience in pre-processing claims data, including Rx (Treatment), Px (Procedure), and Dx (Diagnosis) tables. Knowledge of advanced analytics and machine learning is a plus.

Roles and Responsibilities:

- Analyze and interpret US patient-level claims data from leading vendors such as IQVIA, Health Verity, Komodo, etc.

- Pre-process claims data, applying valid assumptions such as look-back periods for Rx, Px, and Dx tables.

- Perform longitudinal analysis to track patient pathways, treatment adherence, and outcomes over time.

- Analyze patient demographics, health behaviors, and utilization patterns to support segmentation and targeting strategies.

- Extract, clean, and integrate patient-level data from various sources, including claims, EHRs, and registries.

- Collaborate with cross-functional teams to deliver actionable insights and support strategic decision-making.

- Develop and deploy machine learning models for classification, regression, and clustering tasks (good to have).

- Utilize programming languages like Python and SQL for data wrangling, analysis, and visualization.

- Leverage cloud platforms (AWS, Azure) and Databricks to build scalable data solutions (good to have).

Required Skills and Qualification:

- 3-5 years of hands-on experience with US patient-level claims data analytics.

- Strong knowledge of real-world pharma datasets from vendors like IQVIA, Health Verity, Komodo, etc.

- Proficiency in pre-processing Rx, Px, and Dx tables using valid assumptions.

- Familiarity with machine learning techniques and experience with open-source tools is a plus.

- Proficiency in Python and R; experience with Databricks is an advantage.

- Knowledge of cloud platforms like AWS or Azure for data analysis and model deployment is desirable.

- Strong problem-solving skills and attention to detail.

- Excellent communication skills to present findings and insights effectively