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Google Internship Data Science Jobs in Worcester, MA

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 ...

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 ...

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 ...

Apply advanced analytics, decision science, and generative AI to build intelligent products ... Familiarity with Vertex AI and Google Cloud Platform, or equivalent enterprise AI platforms, is ...

Senior Data Engineer-PBM

Woonsocket, RI · On-site

$109K - $131K/yr

Collaborates with data science team to define and build datasets for training of analytic data ... Experience leveraging Cloud Technologies (Google Cloud Platform Preferred, AWS, Azure) for ETL and ...

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Google Internship Data Science information

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How much do google internship data science jobs pay per hour?

As of Aug 23, 2026, the average hourly pay for google internship data science in Worcester, MA is $22.46, according to ZipRecruiter salary data. Most workers in this role earn between $17.26 and $24.47 per hour, depending on experience, location, and employer.

What is a Google internship in data science?

A Google Internship in Data Science is a temporary, paid position where students or recent graduates work with Google's data science teams. Interns are involved in analyzing large datasets, building machine learning models, and providing insights to improve Google products and services. The internship offers hands-on experience, mentorship, and exposure to real-world data science challenges in a leading tech company. Applicants typically need strong analytical skills, proficiency in programming languages like Python or R, and a background in statistics or computer science.

What types of projects does a data science intern typically work on during a Google internship?

Data Science interns at Google often collaborate on high-impact projects alongside full-time data scientists and engineers. Projects may include analyzing large datasets to identify trends, building machine learning models, or developing data-driven solutions for products and services. Interns are encouraged to contribute ideas, participate in code reviews, and present findings to their teams. This hands-on experience allows interns to gain exposure to Google's tools and methodologies, while also building a strong foundation for future roles in data science.

What are the key skills and qualifications needed to thrive as a Google data science intern, and why are they important?

To thrive as a Google Data Science Intern, you need a solid background in statistics, programming (such as Python or R), and data analysis, typically supported by current enrollment in a relevant degree program. Familiarity with tools like SQL, TensorFlow, and data visualization platforms is commonly expected, along with experience in machine learning frameworks. Strong problem-solving abilities, effective communication, and collaboration skills help interns contribute meaningfully to cross-functional teams. These skills are essential to analyze complex datasets, deliver actionable insights, and succeed in Google's fast-paced, innovative environment.

What is the difference between Google Internship Data Science vs Google Data Analyst Internship?

AspectGoogle Internship Data ScienceGoogle Data Analyst Internship
Required SkillsProgramming (Python, R), statistics, machine learning, data modelingData analysis, SQL, Excel, visualization tools
Work EnvironmentCollaborative, research-focused, technical projectsBusiness-oriented, reporting, data interpretation
Industry UsageResearch, product development, machine learning modelsBusiness insights, performance metrics, reporting

Google Internship Data Science roles focus on developing machine learning models and advanced analytics, requiring programming and statistical skills. In contrast, Google Data Analyst Internships emphasize data interpretation, reporting, and visualization for business decisions. Both roles are valuable within Google's data ecosystem but serve different functions based on technical depth and business application.

What are popular job titles related to Google Internship Data Science jobs in Worcester, MA?

For Google Internship Data Science jobs in Worcester, MA, the most frequently searched job titles are:

What cities near Worcester, MA are hiring for Google Internship Data Science jobs?

Cities near Worcester, MA with the most Google Internship Data Science job openings:

Scientist, Data Science

AstraZeneca

Waltham, MA • On-site

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 17 days ago


AstraZeneca rating

8.4

Company rating: 8.4 out of 10

Based on 45 frontline employees who took The Breakroom Quiz

22nd 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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About AstraZeneca

Sourced by ZipRecruiter

AstraZeneca is a global, science-led, patient-focused biopharmaceutical company that focuses on the discovery, development and commercialization of prescription medicines for some of the world's most serious diseases. But we're more than one of the world's leading pharmaceutical companies. A place built on courage, curiosity and collaboration - we make bold decisions driven by patient outcomes. Empowered to lead at every level, free to ask questions and take smart risks that write the next chapter for our pipeline and Oncology team. Make a meaningful impact that brings real benefits to society. By applying your knowledge of data, you will help to redefine our industry and ultimately save lives. Work with experts who share a common goal: to accelerate the potential of medicines and the science of tomorrow.

Industry

Pharmaceutical product wholesalers and pharmaceutical and medicine manufacturing

Company size

10,000+ Employees

Headquarters location

Cambridge, Cambridgeshire, GB