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Novartis Data Scientist Jobs (NOW HIRING)

Novartis

Clinical Data Engineering Lead

Cambridge, MA · On-site

Novartis Biomedical Research is searching for a visionary Associate Director to lead Clinical Data Engineering within their Oncology Data Science team. In this pivotal role, you'll be responsible for ...

Novartis

Clinical Data Engineering Lead

Cambridge, MA

$176K - $327K/yr

Novartis Biomedical Research (NBR) is searching for a visionary Associate Director to lead Clinical Data Engineering within our Oncology Data Science (OncDS) team. In this pivotal role, you'll be at ...

Novartis

Associate Director, Data Science

Cambridge, MA · Hybrid

$160K - $297K/yr

Cambridge, MA Novartis is a leader in data science and model-informed drug development. We are seeking an experienced Data Science leader to advance data-driven drug discovery and development by ...

Novartis

Director, Data Science

East Hanover, NJ · On-site +1

$194K - $312K/yr

The Insights and Decision Science (IDS) team is dedicated to enabling improved decision making at Novartis by leveraging superior data to identify actionable insights that drive enhanced performance.

Publicis Groupe Holdings B.V

Data Scientist

Chicago, IL · On-site

... Novartis, Samsung, Visa and more. Overview The Data Scientist at Starcom will play a hands-on role in creating, testing and scaling analytics solutions within the Databricks environment. Sitting ...

Publicis Groupe Holdings B.V

Data Scientist

Chicago, IL · On-site

... Novartis, Samsung, Visa and more. Overview The Data Scientist at Starcom will play a hands-on role in creating, testing and scaling analytics solutions within the Databricks environment. Sitting ...

Novartis

Senior Expert I, Data Science

San Diego, CA

$126K - $234K/yr

The Low Molecular Weight (LMW) team at Novartis Biomedical Research Oncology Data Science is seeking a highly motivated Senior Computational Scientist to join our team. With a focus on induced ...

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How much do novartis data scientist jobs pay per year?

As of Jul 5, 2026, the average yearly pay for novartis data scientist in the United States is $165,018.00, according to ZipRecruiter salary data. Most workers in this role earn between $133,500.00 and $170,000.00 per year, depending on experience, location, and employer.

What are some typical projects or daily tasks for a Data Scientist at Novartis?

As a Data Scientist at Novartis, you may work on projects such as analyzing clinical trial data, developing predictive models for patient outcomes, or optimizing pharmaceutical processes using advanced analytics. Daily tasks often include data cleaning, exploratory analysis, building and validating models, and presenting your insights to multidisciplinary teams. You’ll collaborate closely with biostatisticians, clinicians, and IT specialists to ensure data-driven decisions support scientific research and business objectives. The role encourages continuous learning and presents opportunities to make a tangible impact on new drug development and patient care.

What is a Novartis Data Scientist job?

A Novartis Data Scientist leverages data analytics, machine learning, and statistical modeling to drive insights that support drug development, clinical trials, and business decisions. They work with large datasets, collaborate with cross-functional teams, and develop algorithms to optimize processes in healthcare and pharmaceuticals. Their role involves cleaning and analyzing data, building predictive models, and communicating findings to stakeholders to improve patient outcomes and operational efficiency.

What are the key skills and qualifications needed to thrive in the Novartis Data Scientist position, and why are they important?

To thrive as a Novartis Data Scientist, you need a solid background in data analysis, statistical modeling, and machine learning, typically coupled with a degree in a quantitative field such as computer science, statistics, or bioinformatics. Familiarity with programming languages like Python or R, experience with data visualization platforms, and knowledge of pharmaceutical industry standards and tools (e.g., SAS, SQL, or cloud computing environments) are strongly preferred. Excellent communication, problem-solving, and collaboration skills help you work effectively with cross-functional teams and convey complex findings to non-technical stakeholders. These competencies are crucial for leveraging data to drive scientific innovation and support business decisions in a regulated and fast-evolving healthcare environment.

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Clinical Data Engineering Lead

Clinical Data Engineering Lead

Novartis

Cambridge, MA • On-site

Full-time

Posted 20 days ago

Novartis rating

7.4

Company rating: 7.4 out of 10

Based on 8 frontline employees who took The Breakroom Quiz

53rd of 73 rated pharmaceutical

Job description

Job Summary:
Novartis Biomedical Research is searching for a visionary Associate Director to lead Clinical Data Engineering within their Oncology Data Science team. In this pivotal role, you’ll be responsible for shaping early clinical development by building innovative biomarker data infrastructure and championing translational research.
Responsibilities:
• Define and implement the clinical data engineering roadmap in alignment with Novartis’ data and digital strategy, collaborating with SMEs and OncDS leadership.
• Integrate advanced tools and AI/ML-ready infrastructure to support predictive modeling, multimodal analytics, and real-world data applications.
• Align clinical and pre-clinical data engineering initiatives with the broader oncology strategy.
• Lead, manage, and develop a high-performing clinical data engineering team, fostering collaboration and growth.
• Drive strategic initiatives and partnerships across a matrixed organization.
• Oversee data ingestion, transformation, and validation processes for clinical trial data, ensuring compliance with GCP/GxP, CDISC, and SOPs.
• Collaborate with CROs and internal teams to optimize data flow, versioning, and retention policies.
• Build and optimize data pipelines for both structured and unstructured clinical data to enable advanced analytics and informed decision-making.
• Deploy scalable solutions for data harmonization, metadata management, and interoperability across platforms such as Foundry, Domino, Snowflake, and POSIT Connect.
• Develop and manage applications and visualization tools, contributing to novel data products that support clinical decision-making and enable AI-driven initiatives in oncology trials.
Qualifications:
Required:
• Master's degree in computer science, Bioinformatics, Data Engineering, Software Engineering or a closely related discipline; PhD preferred.
• Minimum 10 years of hands-on experience architecting and managing clinical data engineering, data management, and bioinformatics solutions in pharmaceutical or biotechnology industry.
• Demonstrated expertise in designing, implementing, and scaling data infrastructure to support clinical development—including Artificial Intelligence (AI) / Machine Learning (ML) -driven analytics and multimodal data integration.
• Proven ability to define, document, and operationalize end-to-end assay data generation and processing pipelines, with a focus on automation, orchestration, and compliance.
• Extensive experience with oncology clinical trials, including regulatory-compliant management of clinical biomarker data and application of data standards (e.g., Clinical Data Interchange Standards Consortium [CDISC], Study Data Tabulation Model [SDTM], Analysis Data Model [ADaM]).
• Deep familiarity with FAIR (Findable, Accessible, Interoperable, Reusable) data principles, data harmonization, and enterprise data governance frameworks.
• Strong leadership in technical teams, with advanced communication and stakeholder management skills.
Preferred:
• Extensive experience leading cross-functional data science initiatives in oncology, including translational science, biomarker analysis, real-world data, and exploratory clinical research; proven expertise with NGS technologies, and modern bioinformatics tools.
• Advanced proficiency in cloud-native architectures, data lakes, and visualization frameworks (e.g., RShiny, Dash, Spotfire); strong programming and engineering skills (R, Python, Java, shell scripting, Linux, HPC), with a deep understanding of GxP, Agile methodologies, AI/ML operations, and architecting/managing AI agents in large clinical data environments.
Company:
Novartis is a pharmaceutical company that researches and develops medicines for serious diseases to improve and extend people's lives. It is a sub-organization of Meye Asset Management. Founded in 1996, the company is headquartered in Basel, CHE, with a team of 10001+ employees. The company is currently Late Stage.

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