SCO-Manufacturing-Data Scientist

At EY, you’ll have the chance to build a career as unique as you are, with the global scale, support, inclusive culture and technology to become the best version of you. And we’re counting on your unique voice and perspective to help EY become even better, too. Join us and build an exceptional experience for yourself, and a better working world for all.

Service line - Position Title:Senior Data Scientist - Pharmaceutical / Life Sciences

(6+ Years Experience)

At EY, we’re all in to shape your future with confidence.

We’ll help you succeed in a globally connected powerhouse of diverse teams and take your career wherever you want it to go.

Join EY and help to build a better working world.

About Global Delivery Services

Global Delivery Services refers to EY's worldwide network of service delivery centers. The GDS team plays an important role in EY’s strategy by ensuring effective support to EY’s growth agenda.

Our journey started in 2002 with approximately 200 people. Today we stand at 80,000+ professionals in ten locations around the world. We operate in Argentina, China, Hungary, India, Philippines, Poland, Sri Lanka, Mexico, Spain and the United Kingdom.

Client service is focused on providing Consulting, Assurance, Tax, Strategy & Transactions, and Knowledge support to our clients around the world. The teams enable account teams worldwide to provide seamless, high-quality, value-added support, helping deliver exceptional client service.

Enablement Services provides cost-effective, high-skilled, and innovative services to support EY’s global and local enablement teams. Markets, BMC, AWS, Finance and Accounting, Risk Management, Procurement, People Shared Services, IT Service Delivery and IT Global Infrastructure services, are among the services offered by Enablement Services.

Our innovation specialists serve the GDS Client Service and Enablement Services teams, along with Service Lines, Core Business Services and Sectors. The team brings the desired environment, technologies and skilled teams together for facilitation, rapid prototyping and innovative thinking. The competencies offered include analytics, digital, user experience, mobile technology, infrastructure, Microsoft technologies and open innovation.

The Opportunity

An opportunity to combine Data Science, AI/ML, and pharmaceutical domain expertise to deliver scalable, data-driven solutions that transform manufacturing, quality, supply chain, and business operations.

Responsibilities

• Design, develop, validate, and deploy data science, machine learning, and advanced analytics solutions to address pharmaceutical business and manufacturing challenges.
• Analyse large, complex datasets to identify patterns, trends, anomalies, and actionable insights.
• Develop predictive and prescriptive models, forecasting solutions, optimization models, and statistical analyses.
• Perform data preprocessing, feature engineering, model development, evaluation, validation, and performance monitoring.
• Collaborate with pharma business, manufacturing, quality, engineering, IT, data engineering, and subject-matter experts to translate business problems into analytical solutions.
• Develop analytics solutions for areas such as manufacturing performance, process optimization, quality, deviation analysis, predictive maintenance, supply chain, and operational excellence, depending on project requirements.
• Build reusable analytical pipelines and work with data engineering teams to establish reliable data pipelines and datasets.
• Apply appropriate AI/ML techniques, including supervised and unsupervised learning, time-series analysis, anomaly detection, clustering, classification, regression, and optimization.
• Evaluate opportunities for Generative AI and Large Language Models (LLMs) where appropriate to the business use case.
• Develop dashboards, visualizations, and data-driven insights to support operational and management decision-making.
• Support deployment and operationalization of models through appropriate MLOps, versioning, monitoring, testing, and model governance practices. Production ML roles commonly include model deployment, monitoring, drift detection, and troubleshooting.
• Ensure solutions involving regulated data follow applicable data governance, security, privacy, validation, and regulatory requirements.
• Clearly communicate complex analytical findings and recommendations to both technical and non-technical stakeholders.
• Perform technical reviews and provide guidance to junior data scientists and analytics team members.

Qualifications

• 6+ years of professional experience in Data Science, Machine Learning, AI, Advanced Analytics, or related areas.
• Bachelor’s or master’s degree in data science, Computer Science, Statistics, Mathematics, Engineering, Bioinformatics, or a related discipline.
• Demonstrated experience applying data science within the pharmaceutical, biotechnology, healthcare, or life sciences domain.
• Strong hands-on experience developing statistical and machine-learning models using real-world datasets.
• Strong programming experience with Python and SQL; experience with R and/or SAS is an advantage. Current pharma/healthcare data science roles commonly seek programming and statistical/data-science expertise.
• Experience working with structured and unstructured datasets and performing data preparation, feature engineering, statistical analysis, and model evaluation.
• Understanding of pharmaceutical processes and regulated data environments.
• Experience collaborating with multidisciplinary business, scientific, engineering, and technology teams.
• Experience taking data-science solutions from proof of concept through production deployment is preferred.
• Experience with pharmaceutical manufacturing/MES data, process data, quality data, laboratory data, or supply-chain data is highly desirable for manufacturing-focused programs.

Technical & Functional Skills

• Data Science & AI
• Machine Learning
• Statistical Modeling
• Predictive Analytics
• Prescriptive Analytics
• Time-Series Analysis & Forecasting
• Anomaly Detection
• Classification & Regression
• Clustering
• Optimization
• Feature Engineering
• Model Evaluation & Validation
• Generative AI / LLM concepts
• Programming & Data
• Python
• SQL
• R / SAS
• Pandas, NumPy
• Scikit-learn
• TensorFlow / PyTorch
• Data Wrangling & Data Preparation
• ETL / Data Pipeline concepts
• API integration concepts
• Data Platforms & MLOps
• Azure / AWS / GCP
• Databricks
• MLflow or equivalent MLOps tooling
• Git / version control
• CI/CD concepts
• Model deployment and monitoring
• Model performance and drift monitoring
• Pharmaceutical Domain
• Pharmaceutical manufacturing processes
• GMP / GxP concepts
• Data Integrity
• Quality and process analytics
• Manufacturing / MES data
• Laboratory / LIMS data
• ERP / Supply Chain data
• Process historian / equipment data
• Regulatory and data-governance awareness
• Professional Skills
• Strong analytical and problem-solving capability
• Ability to translate business problems into data science use cases
• Strong stakeholder-management and consulting skills
• Excellent documentation and presentation skills
• Ability to explain complex AI/ML concepts to business stakeholders
• Ability to independently lead data science workstreams
• Experience mentoring junior data scientists

Preferred Candidate Profile

6+ years of Data Science and AI/ML experience with strong pharmaceutical/life sciences domain knowledge and hands-on expertise in Python, SQL, statistical modelling, machine learning, predictive analytics, data engineering concepts, and productionizing analytical solutions. Experience working with pharmaceutical manufacturing, quality, MES, laboratory, or supply-chain data is highly desirable.

What we offer you

At EY, we’ll develop you with future-focused skills and equip you with world-class experiences. We’ll empower you in a flexible environment, and fuel you and your extraordinary talents in a diverse and inclusive culture of globally connected teams.

Are you ready to shape your future with confidence? Apply today.

To help create an equitable and inclusive experience during the recruitment process, please inform us as soon as possible about any disability-related adjustments or accommodations you may need.

Our Commitment: As a commitment, we persistently endeavour to embody our values, fulfil our purpose, and champion inclusiveness. Our dedication is to cultivate EY into an environment where diverse perspectives are celebrated, creating a supportive atmosphere for individuals to authentically be themselves and contribute their utmost.

Professional Development: From entry-level employees to senior leaders, we believe in continuous learning. We offer opportunities to build new skills, take on leadership roles, and connect and grow through mentorship.

People and Culture: In our dynamic workplace, diversity, equity, and inclusiveness are ingrained in our culture. We're united by a commitment to create an environment where every individual's differences are valued, practices are equitable, fostering a sense of belonging. Our shared values include integrity, respect, teaming, inclusiveness, energy, enthusiasm, courage to lead, and building relationships based on doing the right thing.

Benefits: Embark on a transformative career journey with us and indulge in a suite of premium benefits, encompassing exclusive health and wellness packages, enticing rewards, and cutting-edge learning opportunities that empower you to continually grow and excel in your professional and personal development.

How to Apply: If you are passionate to join us and are aligned with our commitment to building a better working world, we invite you to apply by completing our user-friendly form with personal and professional information and by providing your consent to data privacy.

Successful candidates advance to a competency-based interview. If mutual interest persists, a job offer awaits.

“We are an equal opportunity employer and are committed to Diversity, Equity & Inclusion”.

EY | Building a better working world

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