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Data Science Software Engineer Jobs in Boston, MA

NLP/Linguistics Software Engineer

Somerville, MA · On-site

$125K - $150K/yr

ROLE SUMMARY Babel Street is looking for a Software Engineer to join our Analytics Group. This is ... Take theoretical ideas from linguistics and data science and implement them as practical software ...

Develops and mentors team members to maintain technical excellence in AI/ML, software engineering ... data science, analytics, or AI environment. * Prior experience mentoring or managing talent.

Senior Software Engineer

Boston, MA · On-site

$93K - $147K/yr

We are seeking a Software Engineer to join our Data & AI Engineering team to build modern, scalable ... Strong foundation in computer science fundamentals, including data structures, algorithms, and ...

Sr. Data Engineer

Milford, MA · On-site

$125K - $150K/yr

Document technical specifications, solutions, and processes for future reference Qualifications * 6+ years dynamic experience in data engineering, data science, software development, analytics or ...

Sr. Data Engineer

Milford, MA

$125K - $150K/yr

Document technical specifications, solutions, and processes for future reference Qualifications * 6+ years dynamic experience in data engineering, data science, software development, analytics or ...

Sr. Data Engineer

Milford, MA · On-site

$125K - $150K/yr

Document technical specifications, solutions, and processes for future reference * 6+ years dynamic experience in data engineering, data science, software development, analytics or similar roles

... science products in collaboration with data engineers and software engineers. The role involves conducting analyses to provide actionable business insights and informing statistical or machine ...

Showing results 41-60

Data Science Software Engineer information

See Boston, MA salary details

$48.4K

$141.1K

$193.1K

How much do data science software engineer jobs pay per year?

As of Jul 25, 2026, the average yearly pay for data science software engineer in Boston, MA is $141,096.00, according to ZipRecruiter salary data. Most workers in this role earn between $124,500.00 and $149,600.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Data Science Software Engineer, and why are they important?

To thrive as a Data Science Software Engineer, you need strong proficiency in programming (especially Python or R), a solid understanding of statistics and algorithms, and typically a degree in computer science, data science, or a related field. Familiarity with machine learning frameworks (such as TensorFlow or scikit-learn), data processing tools (like Spark or Hadoop), and cloud platforms (AWS, GCP, or Azure) is essential, as are relevant certifications. Excellent problem-solving abilities, communication skills, and the ability to work collaboratively with cross-functional teams set top performers apart. These competencies are vital for efficiently developing scalable data-driven solutions that drive business insights and innovation.

How does a Data Science Software Engineer typically collaborate with data scientists and other stakeholders on projects?

Data Science Software Engineers play a vital role in bridging the gap between data science and software engineering teams. They work closely with data scientists to translate prototypes and models into scalable, production-ready code, and often collaborate with product managers, analysts, and infrastructure engineers to ensure seamless integration. Regular communication and code reviews are essential, as is an iterative development process to address feedback and ensure solutions meet both technical and business requirements. This cross-functional collaboration helps deliver robust data-driven applications that align with organizational goals.

Which is the hardest field in it?

For a Data Science Software Engineer, the most challenging fields often involve complex machine learning algorithms, large-scale data processing, and advanced statistical analysis. Staying current with rapidly evolving tools like Python, R, and cloud platforms also requires continuous learning and adaptation. These areas demand strong problem-solving skills and deep technical knowledge.

What is a Data Science Software Engineer?

A Data Science Software Engineer is a professional who combines software engineering skills with data science expertise to build scalable data-driven systems and applications. They design, develop, and optimize software that supports data pipelines, machine learning models, and analytics platforms. Their work bridges the gap between data scientists, who focus on statistical analysis and modeling, and traditional software engineers, who focus on building robust and efficient software systems. Data Science Software Engineers ensure that data solutions are production-ready, scalable, and maintainable.

Can a software engineer work as a data scientist?

A software engineer can transition to a data scientist role by developing skills in statistics, machine learning, and data analysis, often using tools like Python, R, and SQL. While the roles have different focuses, software engineers' programming expertise can be a strong foundation for data science work, especially with additional training or experience in data modeling and analytics.

Is 40 too late for data science?

Data science software engineers can enter the field at any age, as success depends on skills, experience, and continuous learning. Many professionals transition into data science later in their careers by acquiring relevant knowledge in programming, statistics, and tools like Python or R. Age is not a barrier if you develop the necessary technical expertise and stay current with industry trends.

What engineers make $500,000?

Senior data science software engineers with extensive experience, advanced skills in machine learning, and proficiency in tools like Python, R, and cloud platforms can reach salaries of $500,000 or more, especially in high-cost-of-living areas or within large tech companies. Compensation often includes base salary, bonuses, and stock options, reflecting their expertise and impact on business outcomes.

What is the difference between Data Science Software Engineer vs Data Analyst?

AspectData Science Software EngineerData Analyst
Required SkillsProgramming, software development, machine learningData visualization, statistical analysis, reporting
Work EnvironmentSoftware development teams, engineering projectsBusiness units, reporting teams
Common ToolsPython, Java, SQL, ML frameworksExcel, Tableau, SQL, R
Industry UsageTech, finance, healthcare, startupsMarketing, finance, retail, research

While both roles analyze data, Data Science Software Engineers focus on developing software solutions and machine learning models, requiring strong programming skills. Data Analysts primarily interpret data through visualization and statistical methods to support business decisions. The roles often overlap but serve different functions within organizations.

What are popular job titles related to Data Science Software Engineer jobs in Boston, MA? For Data Science Software Engineer jobs in Boston, MA, the most frequently searched job titles are:
What job categories do people searching Data Science Software Engineer jobs in Boston, MA look for? The top searched job categories for Data Science Software Engineer jobs in Boston, MA are:
Team Leader in Data Science, Disease Area X

Team Leader in Data Science, Disease Area X

Novartis

Cambridge, MA

Full-time

Medical, Life, Retirement, PTO

Posted 2 days ago


Novartis rating

7.4

Company rating: 7.4 out of 10

Based on 16 frontline employees who took The Breakroom Quiz

57th of 74 rated pharmaceutical


Job description

Job Description Summary

The Team Leader in Data Science, Disease Area X at Novartis will lead and contribute to high-impact data science programs that transform complex biological, translational, and multi-omics data into decision-driving insights for drug discovery. This role will combine scientific leadership, hands-on computational expertise, and people leadership to advance target identification, biomarker discovery, mechanism-of-action understanding, and portfolio decisions.
The successful candidate will lead a multidisciplinary team of data scientists and partner closely with biology, translational research, data sciences, IT, and discovery platform teams. They will help define and operationalize AI/ML strategy for discovery applications, including generative and agentic AI. This leader will also contribute significantly to data generation, curation, and engineering strategies that enable scalable use of proprietary and public datasets. The role reports to the Head of Data Science, Disease Area X.


Job Description

Internal Job Title: Senior Principal Scientist or Associate Director

Position Location: Cambridge, MA Hybrid

Key responsibilities:

  • Lead data science strategy and executionfor hypothesis-driven discovery programs, including study design, analysis of experiments, and interpretation of complex biological datasets.

  • Drive multi-omics analyticsacross genomics, transcriptomics, proteomics, single-cell, spatial, imaging, clinical, and other relevant data modalities to support target and biomarker portfolios.

  • Translate scientific questions into computational strategies, selecting fit-for-purpose statistical, machine learning, AI, and bioinformatics approaches.

  • Operationalize responsible use of generative and/or agentic AI tools in drug discovery workflows, ensuring scientific rigor, data governance, and appropriate human oversight.

  • Contribute hands-on technical workin scientific software development, data engineering, workflow automation, reproducible analysis, and scalable analytical pipelines.

  • Partner cross-functionallywith wet-lab scientists, translational researchers, platform teams, and senior stakeholders to shape experimental design and accelerate decision-making.

  • Prioritize resources and capabilitiesacross multiple projects, adapting to evolving portfolio needs and balancing strategic impact with delivery timelines.

  • Lead, coach, and develop direct reports, creating a collaborative, inclusive, scientifically rigorous, and high-performing team environment.

  • Communicate scientific findings and recommendationsclearly through internal presentations, governance discussions, publications, posters, and external scientific forums.

  • Promote FAIR data practices, reproducible research, high-quality documentation, project tracking, and scalable analytical standards across the team.

Essential Requirements:

  • Advanced degree (PhD preferred) in Data Science, Computational Biology, Bioinformatics, Computational Science, Molecular Biology, Genetics, Biochemistry, Engineering, or a related quantitative or life sciences discipline.

  • 6+ years of relevant experience applying computational biology, bioinformatics, AI/ML, statistics, or data science to drug discovery, translational research, biotechnology, pharmaceutical R&D, technology, or academic research.

  • Experience leading or managing internal data scientists, computational biologists, bioinformaticians, or machine learning scientists in a matrix management environment as well as external collaborators

  • Demonstrated ability to lead complex, hypothesis-driven scientific analyses using biological, multi-omics, or translational datasets, including RNA-seq, single-cell RNA-seq, proteomics, genomics, spatial biology, and/or imaging.

  • Strong practical experience with scientific software development, reproducible analysis, workflow orchestration and collaborative development practices; experience in Python and/or R, with familiarity in tools such as GitHub, HuggingFace, workflow managers, Jupyter notebooks, containers

  • Deep experience with cloud-based or enterprise-scale compute platforms, high-performance computing

  • Significant experience influencing and collaborating across diverse scientific teams, including wet-lab biology, translational research, engineering, and computational functions.

  • Familiarity with modern AI/ML methods and their application to biological or biomedical data (i.e. generative, agentic AI)

  • Experience acquiring, curating, and engineering proprietary and public datasets while maintaining appropriate data governance, privacy, and security standards.

  • Demonstrated ability to shape scientific strategy cross-functionally, influence senior stakeholders, and translate analytical results into portfolio-relevant decisions.

  • Track record of scientific impact through publications, conference presentations, internal decision support, or portfolio contributions.

  • Strong communication, interpersonal, ethical judgment, resilience, and self-awareness skills.

Compensation & Benefits:

The salary for this position is expected to range between $160,300 and $297,700 USD annually for Senior Principal Scientist, Data Science, and $176,400 and $327,600 USD annually for Associate Director, Data Science. The final salary offered is determined based on factors like, but not limited to, relevant skills andexperience, and upon joining Novartis will be reviewed periodically. Novartis may change the publishedsalary range based on company and market factors.


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


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


To learn more about the culture, rewards and benefits we offer our people click here.


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, sex, national origin, age, sexual orientation, gender identity or expression, marital or veteran status, disability, or any other legally protected status.


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 to perform the essential functions of a position, please send an e-mail to us.reasonableaccommodations@novartis.com or 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.


Salary Range

$160,300.00 - $297,700.00


Skills Desired

Artificial Intelligence (AI), Biostatistics, Business Value Creation, Change Management, Curious Mindset, Data Governance, Data Literacy, Data Quality, Data Science, Data Visualization, Deep Learning, Graph Algorithms, Learning Agility, Machine Learning (ML), Machine Learning Algorithms, Python (Programming Language), Stakeholder Engagement, Statistical Analysis, Time Series Analysis

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Benefits

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