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Associate Chemistry Data Science Jobs (NOW HIRING)

... chemistry, data science, and computer science to help us develop a software framework for designing and discovering new advanced materials and chemicals. Work will focus on (1) the application of ...

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Associate Chemistry Data Science information

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How much do associate chemistry data science jobs pay per year?

As of Jun 23, 2026, the average yearly pay for associate chemistry data science in the United States is $68,039.00, according to ZipRecruiter salary data. Most workers in this role earn between $59,000.00 and $59,500.00 per year, depending on experience, location, and employer.

How does an Associate Chemistry Data Science professional typically collaborate with laboratory scientists and other data teams?

As an Associate Chemistry Data Science professional, you’ll frequently work alongside laboratory scientists to translate experimental data into actionable insights. Your role often involves helping to design data collection protocols, cleaning and analyzing large datasets, and presenting findings to both technical and non-technical colleagues. Collaboration is key, as you'll participate in cross-functional meetings, contribute to interdisciplinary projects, and sometimes help train lab staff on new data tools or software. This teamwork fosters a dynamic environment where scientific and analytical skills come together to advance research objectives.

What are the key skills and qualifications needed to thrive as an Associate Chemistry Data Scientist, and why are they important?

To thrive as an Associate Chemistry Data Scientist, you need a solid background in chemistry, data analysis, and programming, typically supported by a degree in chemistry, data science, or a related field. Familiarity with tools and languages such as Python, R, cheminformatics software, and data visualization platforms is essential, along with experience in handling large chemical datasets. Strong problem-solving skills, attention to detail, and effective communication set standout candidates apart in this role. These skills enable accurate data interpretation, support collaborative research, and drive innovative solutions in chemical research and development.

What is an Associate Chemistry Data Science role?

An Associate Chemistry Data Science role typically involves applying data analysis, statistical modeling, and machine learning techniques to chemical data in order to derive insights, optimize processes, or support research and development. Professionals in this role work closely with chemists and other scientists to analyze experimental data, build predictive models, and help design experiments. They may also be responsible for data cleaning, visualization, and the interpretation of complex datasets in the chemical sciences. This position often serves as an entry-level or early-career opportunity for individuals with a background in chemistry, data science, or both.
What cities are hiring for Associate Chemistry Data Science jobs? Cities with the most Associate Chemistry Data Science job openings:
What are the most commonly searched types of Chemistry Data Science jobs? The most popular types of Chemistry Data Science jobs are:
What states have the most Associate Chemistry Data Science jobs? States with the most job openings for Associate Chemistry Data Science jobs include:

$194K - $361K/yr

Full-time

Medical, Life, Retirement, PTO

Posted 27 days ago


Job description

Band

Level 6


Job Description Summary

About the role:
#LI:Onsite
The Oncology Data Science team in Biomedical Research supports the Oncology Disease Area with computational biology, Artificial Intelligence / Machine Learning (AI/ML), and data engineering for novel therapeutics across multiple drug modalities. As integrated scientists and engineers, we apply advanced analytics to pre-clinical and clinical projects, enabling progress in target discovery, drug development, and translational and clinical science.
We seek a Director of Data Science to lead our global team of US and Europe-based data scientists specializing in Low Molecular Weight (LMW) drug development who will guide the LMW data science team, collaborate closely with Oncology stakeholders and Biomedical Research, and introduce innovative data-driven solutions to enhance our LMW portfolio and benefit patients.


Job Description

Key Responsibilities:

  • Lead and develop a global team of US and Europe-based data scientists, driving high-quality data science that is grounded in deep understanding of biology and applicable data science methodologies and approaches.

  • Co-develop and execute a data science strategy to enable and enhance innovation in the LMW drug development space.

  • Closely align with the Oncology Drug Development teams to represent the low molecular weight data science function and ensure effective embedding of data science in drug development teams and alignment on scientific direction.

  • Regularly interface with Oncology Disease Area leaders to align priorities and to effectively deploy resources.

  • Collaborate closely with the Oncology Data Science AI team and other teams such as generative chemistry teams on the development and implementation of innovative machine learning algorithms, AI models, and platforms to enable the delivery of predictive and prescriptive insights.

  • Actively engage with stakeholders within partner functions, such as IT, Chemistry and Technology departments and build strong partnerships and shared projects.

  • As a member of the Oncology Data Science Leadership team, contribute to Oncology Data Science overall direction and management, represent the low molecular weight portfolio as a function.

  • Closely collaborate with Oncology Data Science engineering teams to ensure team adherence to data standards, data governance and data strategy and ensure the application of best practices in analytics and high standards of reproducibility in research across the team.

  • Play a leading role in matrix teams such as Translational Data Science Clusters around disease areas or teams centered around key technologies such as genomics, proteomics, spatial technologies etc.

  • Present and externalize work of the team in conferences, abstracts and scientific journals.

Essential Requirements:

  • This position will be located at the Cambridge, MA site and will not have the ability to be located remotely. This position will require 10% travel as defined by the business (domestic and/ or international).

  • Ph.D. in data science, computational biology or related fields, strong scientific mindset, with a deep understanding of biology, oncology and low molecular weight drug development process.

  • 10+ years of experience in a data science role in oncology drug development.

  • Excellent leadership and management skills, with 5+ years of people management experience in the data science space.

  • Experience with Quality Control (QC) and data analysis for common assays, such as bulk RNA-seq, scRNA-seq and/or chromatin-based assays (ChIP-seq, ATAC-seq, Hi-C).

  • Strong expertise in quantitative and computational biology approaches, general AI/machine learning and statistical modeling techniques and a proven track record of delivering data-driven insights and solutions.

  • Excellent communication skills, with the ability to communicate complex data insights and recommendations to cross-functional teams and stakeholders.

  • Proven history of contributions to the scientific community in the form of papers and/or conference presentations.

Preferred Requirements:

  • Experience with AI/ML approaches specific to the low molecular weight field including computational chemistry and application of generative AI in chemistry.

  • Experience with cell line profiling, shRNA or CRISPR perturbation screens, high content cell imaging, proteomics or in vivo efficacy analysis.

The salary for this position is expected to range between $194,600 and $361,400 per year.

The final salary offered is determined based on factors like, but not limited to, relevant skills and experience, and upon joining Novartis will be reviewed periodically. Novartis may change the published salary range based on company and market factors.

Your compensation will include a performance-based cash incentive and, depending on the level of the role, eligibility to be considered for annual equity awards.

US-based eligible employees will receive a comprehensive benefits package that includes health, life and disability benefits, a 401(k) with company contribution and match, and a variety of other benefits. In addition, employees are eligible for a generous time off package including vacation, personal days, holidays and other leaves.


EEO Statement:

The Novartis Group of Companies are Equal Opportunity Employers. We do not discriminate in recruitment, hiring, training, promotion or other employment practices for reasons of race, color, religion, gender, national origin, age, sexual orientation, gender identity or expression, marital or veteran status, disability, or any other legally protected status. We strive to create an inclusive workplace that cultivates bold innovation through collaboration and empowers our people to unleash their full potential.


Accessibility and reasonable accommodations

The Novartis Group of Companies are committed to working with and providing reasonable accommodation to individuals with disabilities. If, because of a medical condition or disability, you need a reasonable accommodation for any part of the application process, or in order to perform the essential functions of a position, please send an e-mail to tas.nacomms@novartis.com call +1 (877)395-2339 and let us know the nature of your request and your contact information. Please include the job requisition number in your message.
https://www.novartis.com/careers/careers-research/notice-all-applicants-us-job-openings


Salary Range

$194,600.00 - $361,400.00


Skills Desired

Applied Mathematics, Artificial Intelligence (AI), Aws (Amazon Web Services), Big Data, Building Construction, Cloud Computing, Computer Science, Data Governance, Data Literacy, Data Management, Data Quality, Data Science, Data Strategy, Electrical Transformer, Machine Learning (ML), Master Data Management, Professional Services, Python (Programming Language), R (Programming Language), Random Forest Algorithm, Statistical Analysis, Time Series Analysis