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Monday Friday Data Science Internships Jobs (NOW HIRING)

The successful candidate will leverage their data science expertise in mining large datasets to ... Prior experience or internship in the pharmaceutical or biotechnology industry. * Prior experience ...

Posted today

The Data Science and AI Academy's goal is to network and catalyze data science across all three ... Data Internships Preparation for Social Impact * Exploring Machine Learning Appointments will be ...

The Data Science and AI Academy's goal is to network and catalyze data science across all three ... Data Internships Preparation for Social Impact * Exploring Machine Learning Appointments will be ...

Monday - Friday 8am - 5pm (Onsite 4 days a week) (Possible remote for the right candidate) Position Summary: The Staff Data Scientist will be a key role in the Data Science and Analytics team tasked ...

Monday - Friday 8am - 5pm (Onsite 4 days a week) (Possible remote for the right candidate) Position Summary: The Staff Data Scientist will be a key role in the Data Science and Analytics team tasked ...

Data Science Engineer

Livermore, CA · On-site

$121K - $154K/yr

... internships, or research projects). * Demonstrated experience developing generative AI solutions ... Master's degree in Computer Science, Data Science, Engineering, Mathematics, Statistics, or a ...

... internships, or research projects). * Demonstrated experience developing generative AI solutions ... Master's degree in Computer Science, Data Science, Engineering, Mathematics, Statistics, or a ...

... internships, or research projects). * Demonstrated experience developing generative AI solutions ... Master's degree in Computer Science, Data Science, Engineering, Mathematics, Statistics, or a ...

... internship) of engineering or business school, currently pursuing a degree in data science ... Monday - Thursday meals provided in Ardian's office * Open to J1/F1 sponsorship To enhance your ...

Data Science at State Farm: As a Data Scientist at State Farm, you will serve as a subject matter ... Lead/mentor other data scientists, interns, and other technical work teams * Make strategic ...

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Monday Friday Data Science Internships information

What is the difference between Monday Friday Data Science Internships vs Monday Friday Data Analyst Internships?

AspectMonday Friday Data Science InternshipsMonday Friday Data Analyst Internships
Required CredentialsTypically requires a degree in Data Science, Computer Science, or related fieldsUsually requires a degree in Statistics, Business, or related fields
Work EnvironmentFocuses on developing models, algorithms, and predictive analyticsCenters on interpreting data, creating reports, and supporting decision-making
Employer & Industry UsageUsed in tech, finance, and e-commerce sectors for advanced analyticsCommon in marketing, finance, and consulting firms for data reporting

While both internships involve working with data, Data Science Internships focus on building models and algorithms, whereas Data Analyst Internships emphasize data interpretation and reporting. Your choice depends on your skills and career goals in data roles.

More about Monday Friday Data Science Internships jobs
What cities are hiring for Monday Friday Data Science Internships jobs? Cities with the most Monday Friday Data Science Internships job openings:
What are the most commonly searched types of Data Science Internships jobs? The most popular types of Data Science Internships jobs are:
What states have the most Monday Friday Data Science Internships jobs? States with the most job openings for Monday Friday Data Science Internships jobs include:
Infographic showing various Monday Friday Data Science Internships job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 83% Full Time, 12% Part Time, and 4% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution.

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 14 hours ago

Posted today


AstraZeneca rating

8.4

Company rating: 8.4 out of 10

Based on 45 frontline employees who took The Breakroom Quiz

21st of 86 rated pharmaceutical


Job description

We are seeking a highly motivated Scientist to join a newly formed, dynamic team within early oncology R&D. The successful candidate will leverage their data science expertise in mining large datasets to drive our efforts in target identification, mechanism of action (MOA) studies, and biomarker strategy development, with a particular focus on analyses related to the function and aging of the immune system.

At AstraZeneca, you'll have the opportunity to make a significant impact on the future of healthcare while working in a collaborative environment at the cutting edge of research. The ideal candidate will thrive in this setting, contributing to our growth trajectory as we build our evolving team.

Key Responsibilities:

  • Execute and Maintain Pipelines: Process and analyze large-scale biobank datasets, human population data, and in-vitro biological data using established analysis pipelines.

  • Analytical Support: Apply analytical methods and machine learning algorithms to help identify potential therapeutic targets and biomarkers.

  • Cross-Functional Collaboration: Partner with wet-lab scientists to analyze experimental results for target identification and Mechanism of Action (MOA) studies.

  • Data Visualization: Generate high-quality visualizations and reports to communicate findings to the project team.

  • Strategic Contribution: Provide high-quality data and computational insights that contribute to the development of biomarker strategies.

  • Team Participation: Actively participate in team meetings, presenting data-driven insights to help the group meet project milestones.

  • Continuous Learning: Stay current with the latest developments in data science and bioinformatics tools.

Qualifications:

  • Education: Ph.D. in Bioinformatics, Computational Biology, Data Science, Epidemiology, or a related field (0-2 years post-graduate experience); or MS with 2-4 years of experience; or BS with 4+ years of relevant experience.

  • Data Experience: Minimum 2 years of experience working with large-scale biological or population datasets, preferably including experience analyzing immune system aging/function within the context of human and/or mouse data.

  • Coding Proficiency: Strong proficiency in Python or R.

  • Technical Knowledge: Solid understanding of statistical analysis and foundational machine learning techniques.

  • Genomics Foundation: Hands-on experience with NGS data analysis (e.g., RNA-seq, DNA methylation, ChIP-seq, or ATAC-seq).

  • Multi-omics Interest: Experience with, or a strong desire to learn, proteomic data analysis and multi-omic data integration.

  • Operational Skills: Excellent problem-solving skills, attention to detail, and the ability to manage multiple tasks in a fast-paced environment.

  • Communication: Ability to clearly present data and technical workflows to a multidisciplinary team.

Desired Skills and Attributes:

  • Prior experience or familiarity with biomarkers of immune system aging/function.

  • Prior experience or internship in the pharmaceutical or biotechnology industry.

  • Prior experience running large-scale association testing (e.g., genome-wide association studies [GWAS], epigenome-wide association studies [EWAS], proteome-wide association studies).

  • Familiarity with methods in statistical genetics (e.g., Mendelian randomization, fine mapping, colocalization).

  • Familiarity with machine learning analysis architectures (e.g., random forest, gradient boosting, transformers).

  • Familiarity with public biological databases (e.g., GTEx, TCGA), epidemiological cohort data (e.g., TOPMed cohorts), or biobanks (e.g., UK Biobank, FinnGen).

  • Ability to apply integrated generative protein design pipelines - from target-conditioned backbone generation through sequence design to computational fold validation - to support the development of novel therapeutic biologics with optimized specificity and developability properties.

  • Working knowledge of computational histology pipelines incorporating modern deep learning approaches - including self-supervised and weakly supervised learning (MIL, DINO) and histopathology foundation models (e.g. UNI, CONCH) - to enable scalable, label-efficient classification of complex tissue phenotypes.

  • Familiarity or prior experience with agentic AI in the context of analysis code pipeline development and biological analysis.

  • Evidence of scientific contribution through publications, posters, or GitHub repositories.

As AstraZeneca continues to put patients at the forefront of our mission, we are excited for our move to Kendall Square/Cambridge in 2026. Find out more information here: Kendall Square Press Release

Ready to join us on this mission? Apply now!

If you're curious to know more, please contact Bobbi Poole, our Talent Acquisition Partner.

Competitive remuneration and benefits apply

We offer a competitive Total Reward program including a market driven base salary, bonus and long-term incentive. We have a generous paid time off program and a comprehensive benefits package.

The annual base pay for this position ranges from $91,008.80 - $136,513.20. Our positions offer eligibility for various incentives-an opportunity to receive short-term incentive bonuses, equity-based awards for salaried roles and commissions for sales roles.Benefits offered include qualified retirement programs, paid time off (i.e., vacation, holiday, and leaves), as well as health, dental, and vision coverage in accordance with the terms of the applicable plans.

Date Posted

06-Aug-2026

Closing Date

29-Aug-2026

Our mission is to build an inclusive environment where equal employment opportunities are available to all applicants and employees. In furtherance of that mission, we welcome and consider applications from all qualified candidates, regardless of their protected characteristics. If you have a disability or special need that requires accommodation, please complete the corresponding section in the application form.


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