Advisor/Sr. Advisor, Scientific Computing – Bioproduct Research & Developme at Lilly
Indianapolis, IN 46204, USA -
Full Time


Start Date

Immediate

Expiry Date

05 May, 25

Salary

0.0

Posted On

05 Feb, 25

Experience

2 year(s) or above

Remote Job

No

Telecommute

No

Sponsor Visa

No

Skills

Instrumentation, Spotfire, Regulatory Requirements, Gxp, Programming Languages, Working Experience, Data Science, Bioinformatics, Python, Jmp, Experimental Design, Data Systems, R, Matlab, Computational Biology, Biologics, Digital Transformation, Power Bi, Devops, Knime

Industry

Information Technology/IT

Description

At Lilly, we unite caring with discovery to make life better for people around the world. We are a global healthcare leader headquartered in Indianapolis, Indiana. Our employees around the world work to discover and bring life-changing medicines to those who need them, improve the understanding and management of disease, and give back to our communities through philanthropy and volunteerism. We give our best effort to our work, and we put people first. We’re looking for people who are determined to make life better for people around the world.
Actual compensation will depend on a candidate’s education, experience, skills, and geographic location. The anticipated wage for this position is
$121,500 - $228,800

Responsibilities

Hands-on development and implementation of automated data analysis solutions for lab workflows, bridging scientific expertise with advanced computing capabilities to accelerate pharmaceutical development and manufacturing processes.
1. Scientific Data Analysis Pipeline: Streamline, develop, and scale complex scientific data transformation and analysis, including chromatography, mass spectrometry, and multi-detector data. Harmonize and standardize analysis workflows across teams.
2. Morden Data Management: Implement quality control checks and chain of custody to meet regulatory compliance for data integrity. Automate workflows for method transfer, validation, and data integrity compliance.
3. Disruptive Technologies: Apply AI/ML models to enhance data analysis, interpretation, and predictive capabilities. Continuously evaluate and adopt state-of-the-art tools and methodologies for innovative solutions.

Loading...