Data Science Associate

Description

 

 

Granules Pharmaceuticals Inc., (GPI) is a subsidiary of Granules India LTD.  Over the past 34 years, we have worked towards strengthening our core and we are currently the 10th fastest growing generic pharma company in the US!With our sites in Chantilly and Manassas, Virginia, we have R&D through manufacturing and packaging of our medicines including pulsatile drug release in tablet and capsule dosage form, orally disintegrating modified release tablets (XR, MR, ER), modified release suspension and controlled substances capabilities in an abuse deterrent technology platform.We are dedicated to excellence in manufacturing, quality, and commercialization of generic drugs to give customers reliable and affordable options. The Facility Maintenance Technician is responsible for carrying out necessary equipment, buildings and ground repairs (i.e., Boilers, chillers, compressors) including facility PMs, and utility operations associated with our facilities. Ensure the continued efficient operation of Granules Pharmaceuticals Inc. by providing service and support to all equipment, and all manufacturing areas in order to keep our facilities in compliance with GMP standards.

Responsibilities include but not limited to:

• Conduct exploratory data analysis to identify trends, patterns, and improvement opportunities.
• Perform data cleaning and preprocessing to prepare datasets for modeling and reporting.
• Build and evaluate predictive models to support decision-making across operations.
• Create dashboards and reports for data storytelling to communicate insights to business stakeholders.
• Collaborate with cross-functional teams on data pipeline integration and analytics enablement.
• Provide data-driven recommendations that improve operational efficiency, accuracy, and business outcomes.
• Assist in analytics tasks related to system implementations, process changes, or technology upgrades.

Requirements

  

 
Required Experience & Education 

• Master’s Degree in Data Science, Analytics, Statistics, Computer Science, or a related quantitative field preferred
•  Bachelor’s Degree in a STEM discipline with strong analytical coursework (required)
•  Coursework or academic projects in machine learning, statistics, data engineering, optimization, or operations analytics.
• Exposure to cloud computing, database systems, or business analytics is a plus.
• Capstone, thesis, or applied research demonstrating hands-on data work is strongly preferred.

 Required Knowledge & Skills 

• Curiosity & Learning Mindset — eagerness to explore new tools, methods, and business domains.
• Communication — explaining technical concepts to non-technical stakeholders.
• Analytical Thinking — ability to break down complex problems into structured analytical steps.
•  Machine Learning Fundamentals — regression, classification, clustering, model evaluation, and basic time-series concepts.
• Database Concepts — relational databases, SQL querying, joins, indexing, and basic data modelling.
•  Cloud & Modern Data Platforms — familiarity with AWS, Azure, or GCP services for analytics
• Business & Operational Understanding — ability to interpret data in the context of business processes, KPIs, and operational goals.