Sr Data Scientist

BioPharma Consulting JAD Group

About The Position

The Sr. Data Scientist will lead advanced analytics initiatives and partner with cross‑functional teams—including Commercial Insights, Manufacturing, Supply Chain, Engineering, Data Teams, External Vendors, Service Owners, and IS partners—to design and implement analytical models that solve complex business challenges across the PR Operations Organization. This role is responsible for end‑to‑end project execution, from problem definition and methodology selection to model development, deployment, and communication of insights. The Sr. Data Scientist will drive innovation and deliver measurable business impact through strategic use of data science, machine learning, and artificial intelligence.

Requirements

Background in Data Science, Engineering, Mathematics, Applied Physics, Statistics, or Operations Research.
Proven experience leading and executing analytics projects end‑to‑end.
Strong experience with relational, SQL, and graph databases.
Programming proficiency in Python, R, or SAS; familiarity with ML libraries such as scikit‑learn, MLlib, Keras, TensorFlow, PyTorch, etc.
Ability to write well‑abstracted, reusable code; comfortable working in Linux environments.
Strong logical reasoning, problem‑solving, and decision‑making skills.
Excellent organizational skills and ability to manage large, complex datasets.
Ability to collaborate and influence cross‑functional partners to drive analytics initiatives.
Exceptional communication skills with the ability to translate complex analysis into clear, actionable insights.
Experience with distributed computing tools (Spark, Hive, etc.) and large‑scale data environments.
Passion for continuous learning and staying current with advanced analytics trends.
Doctorate OR Master’s + 2 years of experience in data science, statistics, data mining, applied mathematics, business analytics, engineering, computer science, or related fields OR Bachelor’s + 4 years of experience in related fields OR Associate’s + 8 years of experience in related fields OR High School/GED + 10 years of experience in related fields

Nice To Haves

Experience in biotech or pharmaceutical environments preferred.
Experience supporting manufacturing operations ; vial filling experience highly preferred.
Experience deploying or integrating AI solutions into manufacturing or operational environments.
Strong foundation in artificial intelligence, software development, and digital technologies.
Hands‑on experience developing AI/ML models for process optimization or task automation.
Knowledge of Machine Learning, Deep Learning, Generative AI, and Large Language Models (LLMs).
Experience with Python, TensorFlow, PyTorch, OpenCV, or similar AI/ML frameworks.
Basic statistical analysis skills using JMP or similar tools.
Experience generating technical documentation, protocols, reports, and development records.
Knowledge of Good Documentation Practices (GDP), quality systems, and compliance requirements.
Strong project management and problem‑solving capabilities.
Ability to communicate effectively with both technical and non‑technical stakeholders.
Quality‑focused mindset with strong attention to detail.
High digital literacy and proficiency with AI tools and modern technologies.

Responsibilities

Lead, develop, and apply data science, machine learning, and AI capabilities across operational and commercial functions.
Serve as project lead within cross‑functional teams to generate insights that deliver substantial business value.
Work independently with minimal supervision, proactively identifying analytical opportunities.
Conduct business needs assessments, perform SWOT analyses, propose analytical approaches, secure stakeholder alignment, and execute projects end‑to‑end.
Build high‑performance algorithms, prototypes, predictive models, and proof‑of‑concepts using Python.
Develop and execute SQL and other database queries across relational and graph databases.
Collaborate with stakeholders to define methodologies and analytical frameworks that address specific business questions.
Present analytical concepts, project updates, and results in a clear, compelling, and actionable manner.
Create strong data‑driven narratives and presentations using PowerPoint; demonstrate proficiency in Excel and the MS Office suite.
Ensure compliance with regulatory, security, and privacy requirements related to data assets.