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Data Scientist – Technical Services & Manufacturing Sciences

Eli Lilly

Data Scientist – Technical Services & Manufacturing Sciences

Eli Lilly

India, Hyderabad

·

On-site

·

Full-time

·

1w ago

Required Skills

Statistical modeling

Machine learning

Python

R

Data integration

Data quality assurance

GMP knowledge

Regulatory compliance

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.

Data Scientist – Technical Services & Manufacturing Sciences (TSMS)

Company Overview

Lilly, a leading innovation-driven corporation is developing a growing portfolio of pharmaceutical products by applying the latest research from its own worldwide laboratories and from collaborations with eminent scientific organizations. Headquartered in Indianapolis, Indiana, Lilly makes life better – through medicines and information – for some of the world’s most urgent medical needs. Founded over 145 years ago, the company has sustained a culture that values excellence, integrity and respect for people. This has resulted in Lilly frequently being ranked as one of the best companies in the world at which to work. Lilly knows its business has prospered because of its employees – people with a talent for innovation and a passion for making a difference by finding treatments for the most stubborn diseases; people whose talent is matched by their generosity, and people with strong values and a determination to prevail, regardless of the challenges. Join our team – and make a difference in improving health for people all over the world!

Manufacturing and Quality Technical Hub Hyderabad

Lilly has made a strategic investment of more than $1B dollars to establish a Manufacturing and Quality technical hub. This hub will oversee the significant investment in contract manufacturing of starting materials and intermediates for API manufacturing in India and the technical services responsible for managing the scientific agenda for manufacturing and quality. The hub will be recruiting top talent in the areas of process engineering, chemistry, analytical and data sciences to build a cutting-edge scientific organization supporting the exciting manufacturing portfolio of Lilly.

Role Overview:The Data Scientist – TSMS is responsible for delivering advanced analytics, predictive modelling, and digital innovation to support manufacturing and development processes across pharmaceutical operations. This role enables data-driven decision-making, process optimization, and compliance by partnering with global teams, site SMEs, and IT/digital functions. The Data Scientist manages analytics solution delivery, supports digital transformation, and ensures alignment with regulatory and business objectives.

Key Responsibilities:

  • Build, validate, and maintain multivariate statistical models (e.g., PCA/PLS) for real-time process monitoring
  • Lead development and deployment of predictive models and multivariate analytics for process monitoring, anomaly detection, and performance optimization
  • Collaborate with cross-functional teams (manufacturing, R&D, quality, IT) to design and implement data-driven solutions
  • Work with Information Technology teams at Lilly to deliver secure, scalable analytics products (dashboards, data products, model services) and manage project interdependencies
  • Support integration and harmonization of data across PLM, MES, LIMS, ERP, and analytics platforms
  • Ensure data quality, integrity, and compliance with GMP and regulatory standards
  • Facilitate knowledge transfer, training, and adoption of analytics solutions across global teams
  • Track and report analytics project progress, risks, and outcomes to leadership and stakeholders
  • Partner with technical teams to resolve data gaps, inconsistencies, and support validation activities
  • Leverage data visualization and reporting tools (Power BI, Tableau, Seeq) for actionable insights
  • Identify and implement process improvements and automation opportunities for digital transformation
  • Maintain documentation, best practices, and knowledge repositories for analytics solutions
  • Monitor adoption KPIs, gather user feedback, and drive continuous improvement in analytics capabilities

Required Skills and Experience

Technical and Functional Skills:

  • Proficient in statistical modeling, machine learning, coding languages, and predictive analytics (Python, R, SIMCA, JMP)
  • Experienced in data integration, data quality assurance, and digital solution delivery
  • Skilled in data visualization and reporting (Power BI, Tableau, Smartsheet)
  • Knowledgeable in GMP, data integrity, and regulatory compliance.
  • Experience working in Pharmaceutical manufacturing, Research & Development or other similar scientific environments
  • Strong problem-solving, analytical, and detail-oriented mindset
  • Effective communicator with experience working in global, cross-functional teams
  • Ability to communicate complex insights to both technical and non-technical stakeholders
  • Change-oriented and proactive in driving digital transformation
  • Practical problem-solver who can work independently and within cross-functional teams; skilled at stakeholder management and communication
  • Familiarity with cloud analytics (Azure/AWS), data pipelines, and APIs; experience with NLP for unstructured manufacturing knowledge is a plus

Education & Experience:

  • Master’s or Ph.D. in Data Science, Statistics, Engineering, Life Sciences, or related field
  • 5+ years of experience in data science, analytics, or digital deployment in pharmaceutical or life sciences industry
  • Experience in pharmaceutical GMP operations and TSMS or process development; strong understanding of manufacturing unit operations and process monitoring concepts

Additional Information:

  • 10 – 20% travel may be required
  • Some off-shift work (night/weekend) may be required to support 24/7 operations across global supplier network

Lilly is dedicated to helping individuals with disabilities to actively engage in the workforce, ensuring equal opportunities when vying for positions. If you require accommodation to submit a resume for a position at Lilly, please complete the accommodation request form (https://careers.lilly.com/us/en/workplace-accommodation) for further assistance. Please note this is for individuals to request an accommodation as part of the application process and any other correspondence will not receive a response.

Lilly does not discriminate on the basis of age, race, color, religion, gender, sexual orientation, gender identity, gender expression, national origin, protected veteran status, disability or any other legally protected status.

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About Eli Lilly

Eli Lilly

Eli Lilly

Public

Eli Lilly and Company, doing business as Lilly, is an American multinational pharmaceutical company headquartered in Indianapolis, Indiana, with offices in 18 countries. Its products are sold in approximately 125 countries.

10,001+

Employees

India

Headquarters

Reviews

3.7

1 reviews

Work Life Balance

3.0

Compensation

4.2

Culture

2.5

Career

4.0

Management

3.0

65%

Recommend to a Friend

Pros

Higher base pay

Higher bonus target

Supervisory experience opportunities

Cons

Less PTO to start

Toxic culture concerns

Uncertainty about future performance

Salary Ranges

46 data points

Senior/L5

Senior/L5 · Advisor - Advanced Analytics and Data Science

2 reports

$202,627

total / year

Base

$155,868

Stock

-

Bonus

-

$202,627

$202,627

Interview Experience

2 interviews

Difficulty

2.5

/ 5

Duration

14-28 weeks

Offer Rate

100%

Experience

Positive 50%

Neutral 50%

Negative 0%

Interview Process

1

Application Review

2

HR Screen

3

Phone/Video Interview

4

Hiring Manager Interview

5

Final Interview/Panel

6

Offer

Common Questions

Behavioral/STAR

Past Experience

Culture Fit

Industry Knowledge

Technical Knowledge