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Data Science Jobs in Harvard, MA (NOW HIRING)

AstraZeneca

Scientist, Data Science

Waltham, MA · On-site

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 ...

AstraZeneca

Scientist, Data Science

Waltham, MA

$91K - $136K/yr

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 ...

AstraZeneca

Scientist, Data Science

Waltham, MA · On-site

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 ...

Varsity Tutors

Data Science Tutor

Lawrence, MA · Remote

$18 - $40/hr

About the Job The Varsity Tutors Live Learning Platform has thousands of students looking for online Data Science tutors nationally. As a tutor on the Varsity Tutors Platform, you'll have the ...

Varsity Tutors

Data Science Tutor

Lowell, MA · Remote

$18 - $40/hr

About the Job The Varsity Tutors Live Learning Platform has thousands of students looking for online Data Science tutors nationally. As a tutor on the Varsity Tutors Platform, you'll have the ...

Varsity Tutors

Data Science Tutor

Waltham, MA · Remote

$18 - $40/hr

About the Job The Varsity Tutors Live Learning Platform has thousands of students looking for online Data Science tutors nationally. As a tutor on the Varsity Tutors Platform, you'll have the ...

Varsity Tutors

Data Science Tutor

Newton, MA · Remote

$18 - $40/hr

About the Job The Varsity Tutors Live Learning Platform has thousands of students looking for online Data Science tutors nationally. As a tutor on the Varsity Tutors Platform, you'll have the ...

Boseallaboutme

Sr. Data Scientist

Framingham, MA · On-site

$120K - $165K/yr

Data science, machine learning, and analytics are a crucial part of this mission. These capabilities fuel the creation of new and innovative products, helping us to bring the right products to the ...

Bose Corporation

Sr. Data Scientist

Framingham, MA · On-site

$120K - $165K/yr

Data science, machine learning, and analytics are a crucial part of this mission. These capabilities fuel the creation of new and innovative products, helping us to bring the right products to the ...

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All JobsData Science JobsData Science Jobs in Harvard, MA

Data Science information

See Harvard, MA salary details

$38.2K

$125.2K

$200.4K

How much do data science jobs pay per year?

As of Aug 19, 2026, the average yearly pay for data science in Harvard, MA is $125,162.00, according to ZipRecruiter salary data. Most workers in this role earn between $100,400.00 and $138,700.00 per year, depending on experience, location, and employer.

What is data science?

Data science is an interdisciplinary field that uses scientific methods, algorithms, and systems to extract insights and knowledge from structured and unstructured data. It combines skills from statistics, computer science, and domain expertise to analyze and interpret complex data sets. Data scientists work with large amounts of data to identify patterns, make predictions, and help organizations make data-driven decisions.

What does a data scientist do?

As a Data Scientist, you are qualified to work in such diverse fields as research and development, politics, advertising and marketing, technology, healthcare, government, and higher education as well as multiple others. In general, your duties and responsibilities will be to compile and analyze relevant statistics and turn those numbers into algorithms that reveal insights that can be used by other researchers in their areas of study. Data Science can reveal things like consumer buying habits or the likelihood of success for a course of action. Other duties might vary, depending on your unique field of specialty. Related areas in which a Data Scientist might wish to focus include work as a Data Analyst, Machine Learning Engineer, and Project Manager.

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

To thrive as a Data Scientist, you need a strong background in statistics, programming (often Python or R), and data analysis, usually supported by a degree in a quantitative field. Familiarity with machine learning libraries (like scikit-learn or TensorFlow), big data tools (such as Hadoop or Spark), and data visualization platforms is typically required. Critical thinking, problem-solving, and effective communication are vital soft skills for translating complex data insights into actionable business strategies. These skills and qualities are essential for extracting value from data, driving informed decisions, and effectively collaborating with multidisciplinary teams.

What are some common challenges faced by data scientists when working with real-world datasets?

Data scientists often encounter challenges such as missing or inconsistent data, unstructured formats, and noisy information in real-world datasets. Cleaning and preprocessing data to ensure its quality can be time-consuming but is critical for building accurate models. Additionally, data scientists may work closely with domain experts and other team members to better understand the data's context and ensure their analyses align with business objectives. Overcoming these challenges requires strong problem-solving skills and effective collaboration within cross-functional teams.

What is the difference between Data Science vs Data Analyst?

AspectData ScienceData Analyst
Required skillsStatistics, programming (Python, R), machine learningData visualization, SQL, basic statistics
Work environmentDeveloping models, predictive analytics, researchReporting, data cleaning, descriptive analysis
Tools usedPython, R, Jupyter, TensorFlowExcel, SQL, Tableau, Power BI
Industry usageTech, finance, healthcare, e-commerceRetail, marketing, finance, healthcare

Data Science and Data Analyst roles often overlap but differ mainly in scope. Data Scientists focus on building predictive models and advanced analytics, requiring programming and machine learning skills. Data Analysts primarily handle data cleaning, reporting, and visualization. Both roles are essential in data-driven industries, but Data Science is more technical and research-oriented, while Data Analysis emphasizes interpreting data for business insights.

Is a data scientist in high demand?

Data scientists are in high demand across many industries due to the increasing reliance on data-driven decision making. The role requires skills in programming, statistics, and machine learning, and job growth is expected to continue as organizations expand their data capabilities.

What jobs can a data scientist do?

A data scientist can work in roles such as data analyst, machine learning engineer, data engineer, or business intelligence analyst. These roles involve analyzing large datasets, developing predictive models, and using tools like Python, R, and SQL to support decision-making across various industries.
More about Data Science jobs

What are popular job titles related to Data Science jobs in Harvard, MA?

For Data Science jobs in Harvard, MA, the most frequently searched job titles are:

What cities near Harvard, MA are hiring for Data Science jobs?

Cities near Harvard, MA with the most Data Science job openings:

Data Science jobs near you
Infographic showing various Data Science job openings in Harvard, MA as of August 2026, with employment types broken down into 1% As Needed, 84% Full Time, 12% Part Time, and 3% Contract. Highlights an 85% Physical, 4% Hybrid, and 11% Remote job distribution, with an average salary of $125,162 per year, or $60.2 per hour.

Scientist, Data Science

AstraZeneca

Waltham, MA • On-site

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 13 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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