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Temporary Machine Learning Scientist Jobs in Boston, MA

We are currently looking for a Machine Learning Scientist/Researcher to join our team. We would like to advance our current methods of identifying brain activity, using novel machine learning ...

We are currently looking for a Machine Learning Scientist/Researcher to join our team. We would like to advance our current methods of identifying brain activity, using novel machine learning ...

Experience adapting novel machine learning approaches (e.g., from academic literature) to new data sets and problems * Experience with standard data science tools such as scikit-learn, Pandas, and ...

Machine Learning Engineer

Burlington, MA · Remote

$165K - $200K/yr

Partner with Data Scientists to transform research algorithms into robust, production-quality software. * Implement machine learning algorithms in high-performance C++ and Python with a focus on ...

Showing results 21-40

Temporary Machine Learning Scientist information

What is the difference between Temporary Machine Learning Scientist vs Data Scientist?

AspectTemporary Machine Learning ScientistData Scientist
CredentialsTypically requires a master's or PhD in computer science, data science, or related fields; experience with machine learning frameworksUsually holds a bachelor's or master's in data science, statistics, or related fields; strong analytical skills
Work EnvironmentProject-based, often contract roles in tech, finance, or healthcare companiesFull-time or contract roles across various industries, focusing on data analysis and insights
Employer UsageHired for specialized machine learning projects, prototypes, or research tasksEngaged in data analysis, reporting, and building predictive models

In summary, a Temporary Machine Learning Scientist focuses on developing and implementing machine learning models on a temporary basis, often requiring advanced credentials and specialized skills. In contrast, a Data Scientist has a broader role in analyzing data and generating insights, with less emphasis solely on machine learning techniques.

What is a temporary machine learning scientist?

Temporary Machine Learning Scientists are professionals hired on a short-term basis to develop, implement, and optimize machine learning models within an organization. They typically work on specific projects or to fill a temporary gap in expertise, often collaborating with data scientists, engineers, and stakeholders. Their responsibilities may include data preprocessing, feature engineering, model selection, and evaluation. These roles are ideal for projects with defined timelines or exploratory research that does not require a permanent hire. Temporary contracts can range from a few months to a year, depending on the project's scope and needs.

What types of projects do temporary machine learning scientists typically work on, and how do they integrate with existing teams?

Temporary Machine Learning Scientists are often brought in to support short-term projects such as data analysis, model prototyping, or improving existing machine learning pipelines. Their work usually involves collaborating closely with data engineers, software developers, and product managers to ensure seamless integration of models into production systems. Since the role is temporary, effective communication and quick adaptation to the team's workflow are crucial. These scientists are expected to rapidly understand the company's data and objectives, deliver actionable insights, and document their work for team continuity after their contract ends.

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

To thrive as a Temporary Machine Learning Scientist, you typically need advanced knowledge of machine learning algorithms, data analysis, programming skills (such as Python or R), and a relevant degree in computer science or a related field. Familiarity with frameworks like TensorFlow, PyTorch, and tools for data processing and model deployment is often required, along with experience using cloud platforms such as AWS or Azure. Strong problem-solving abilities, adaptability, and effective communication skills help you quickly integrate into teams and deliver results on short-term projects. These skills ensure you can efficiently contribute to impactful solutions and adapt to rapidly changing project requirements.

What are the most commonly searched types of Machine Learning Scientist jobs in Boston, MA?

The most popular types of Machine Learning Scientist jobs in Boston, MA are:

What are popular job titles related to Temporary Machine Learning Scientist jobs in Boston, MA?

For Temporary Machine Learning Scientist jobs in Boston, MA, the most frequently searched job titles are:

What job categories do people searching Temporary Machine Learning Scientist jobs in Boston, MA look for?

The top searched job categories for Temporary Machine Learning Scientist jobs in Boston, MA are:

Infographic showing various Temporary Machine Learning Scientist job openings in Boston, MA as of July 2026, with employment types broken down into 17% Internship, and 83% Full Time. Highlights an 68% In-person, and 32% Remote job distribution.

Applied AI and Machine Learning Scientist (Director)

Pfizer, Inc.

Cambridge, MA • On-site

Full-time

Medical, Dental, Vision, Retirement, PTO

This job post has expired today. Applications are no longer accepted.


Pfizer rating

8.2

Company rating: 8.2 out of 10

Based on 125 frontline employees who took The Breakroom Quiz

32nd of 86 rated pharmaceutical


Job description

Role Summary
The successful candidate for the Applied AI / ML scientist position leads the technical evaluation, development, and application of AI across the Internal Medicine Research Unit (IMRU), translating advances in foundation models, agentic systems, multimodal AI, and related methods into reusable capabilities that strengthen scientific decision-making end-to-end. The role combines deep technical credibility with strong scientific judgment and is accountable for shaping the AI portfolio within the newly created AI for IM Discovery (AIM2) Discovery Center within the IMRU, defining governance and evaluation standards, assessing AI/ML capabilities in external (or internal) partnerships, and accelerating practical AI adoption across IMRU.
This role is intended for a technically credible AI leader who can operate at the interface of machine learning, computational biology, and drug discovery, while remaining grounded in the realities of scientific decision-making. Success will require setting a clear strategy, directing high-value use cases, ensuring that solutions and partnerships are scientifically robust and trusted, and building reusable capabilities that improve the speed, quality, and coherence of evidence generation across the portfolio.
Role responsibilities
  • Provide AI/ML technical leadership for AIM2 and define a clear roadmap for how large language models, agentic systems, multimodal AI, and related methods will be applied to high-value scientific problems across Internal Medicine Research Unit (IMRU).
  • Lead the technical evaluation and development of the AI capabilities in the AIM2, identifying, prioritizing, and shaping opportunities so that AIM2 focuses on areas where technically credible, reusable AI capabilities can create meaningful scientific or operational leverage.
  • Provide senior technical and scientific direction across AIM2 Discovery Center, ensuring that proposed solutions are methodologically sound, fit for purpose, and grounded in biological, translational, and drug discovery context.
  • Guide the development of reusable AI-enabled capabilities that strengthen scientific decision-making end-to-end, with emphasis on scientific rigor, technical quality, reproducibility, and practical utility across IMRU lines.
  • Establish governance and evaluation standards for AI-built capabilities, including expectations for provenance, validation, guardrails, responsible use, and appropriate human oversight.
  • Partner closely with IMRU Integrative Biology, IMRU line teams, MLCS, and Digital partners to ensure that AI efforts remain tightly aligned to real scientific needs and can be deployed in ways that are trusted, scalable, and adopted in day-to-day work.
  • Shape and manage selected external partnerships relevant to AIM2 priorities, helping evaluate emerging technologies and collaborators while ensuring that external engagements remain aligned to Pfizer priorities and IMRU needs.
  • Articulate the value and impact of the AI capabilities within IMRU to senior stakeholders, including technical differentiation, adoption trajectory, and return on investment of key initiatives to support strategic planning and decision making
  • Build a strong technical culture within AIM2 and across IMRU, fostering scientific curiosity, high standards, collaboration, and continuous learning, while helping raise confidence in the responsible application of AI across IMRU.

BASIC QUALIFICATIONS
  • Advanced degree in computer science, machine learning, artificial intelligence, computational biology, bioinformatics, statistics, engineering, life sciences, or a related quantitative or scientific field preferred.
  • Typically, candidates at this level will bring substantial relevant experience, for example approximately 9+ years with a Master's degree, 10+ years with a Bachelor's degree, or 7+ years with a PhD, while recognizing that the right mix of scope, technical depth, scientific credibility, and impact matters more than degree alone.
  • Demonstrated experience leading complex, cross-functional initiatives in applied AI, computational science, data science, digital transformation, or related domains, ideally with responsibility for strategy, portfolio prioritization, and value realization.
  • Strong hands-on understanding of LLMs, foundation models, generative AI, machine learning, and related AI approaches, with the technical credibility to guide decisions, assess trade-offs, and challenge weak approaches even when not serving as the primary builder.
  • Demonstrated ability to identify, prioritize, and shape high-value use cases in ambiguous environments, translating scientific or stakeholder needs into practical, reusable solutions with measurable impact.
  • Experience building and scaling reusable workflows, methods, products, or platforms rather than delivering isolated one-off analyses.
  • Demonstrated ability to develop strategy, shape AI portfolios, and communicate impact and return on investment to senior stakeholders in a clear and credible way.
  • Strong matrix leadership, communication, and influence skills, including the ability to align senior stakeholders, provide technical and strategic direction, and drive adoption without relying solely on formal authority.
  • Sound judgment regarding methodological rigor, evaluation, provenance, model limitations, risk, and the appropriate role of human oversight in AI-enabled scientific workflows.

PREFERRED QUALIFICATIONS
  • Experience in life sciences, pharma, biotech, translational science, omics, or related research environments.
  • Experience and/or training in cardiovascular, metabolic, or obesity biology.
  • Demonstrated ability to operate fluently across AI / technology and biology, grounding technical solutions in scientific reality and engaging credibly with scientists and line leaders.
  • Experience with AI adoption, productization, governance, or workflow transformation in complex, matrixed, regulated organizations.
  • Familiarity with scientific evidence synthesis, literature and document workflows, retrieval-augmented approaches, multimodal AI, or agentic systems applied to scientific problems.
  • Experience working with external technology partners, vendors, or academic collaborators to evaluate, shape, or deploy AI capabilities.
  • Evidence of an entrepreneurial, product-minded approach, including spotting opportunities, making pragmatic trade-offs, iterating rapidly, and turning promising concepts into durable capabilities that are reused and adopted.

ORGANIZATIONAL RELATIONSHIPS
Director of AIM2; AIM2 Innovation Fellows; CSO IMRU; Head of IMRU Integrative Biology; Integrative Biology Scientists; IMRU biology line teams; Integrative Biology and Digital ecosystem partners; AI/ML practitioners, computational biologists, translational scientists, portfolio and strategy stakeholders, and other leaders involved in AI prioritization, deployment, governance, and adoption.
External:
May interact, as appropriate, with external technology partners, vendors, or academic / industry collaborators relevant to AI capability evaluation, development, and adoption.
Candidate demonstrates a breadth of diverse leadership experiences and capabilities including: the ability to influence and collaborate with peers, develop and coach others, oversee and guide the work of other colleagues to achieve meaningful outcomes and create business impact.
This is a hybrid role requiring you to live within commuting distance and work on-site an average of 2.5 days per week.
#LI-PFE
The annual base salary for this position ranges from $176,600.00 to $294,300.00. In addition, this position is eligible for participation in Pfizer's Global Performance Plan with a bonus target of 20.0% of the base salary and eligibility to participate in our share based long term incentive program. We offer comprehensive and generous benefits and programs to help our colleagues lead healthy lives and to support each of life's moments. Benefits offered include a 401(k) plan with Pfizer Matching Contributions and an additional Pfizer Retirement Savings Contribution, paid vacation, holiday and personal days, paid caregiver/parental and medical leave, and health benefits to include medical, prescription drug, dental and vision coverage. Learn more at Pfizer Candidate Site - U.S. Benefits | (uscandidates.mypfizerbenefits.com). Pfizer compensation structures and benefit packages are aligned based on the location of hire. The United States salary range provided does not apply to Tampa, FL or any location outside of the United States.
Relocation assistance may be available based on business needs and/or eligibility.
Candidates must be authorized to be employed in the U.S. by any employer.
U.S. work visa sponsorship (such as TN, O-1, H-1B, etc.) is not available for this role now or in the future.
Sunshine Act
Pfizer reports payments and other transfers of value to health care providers as required by federal and state transparency laws and implementing regulations. These laws and regulations require Pfizer to provide government agencies with information such as a health care provider's name, address and the type of payments or other value received, generally for public disclosure. Subject to further legal review and statutory or regulatory clarification, which Pfizer intends to pursue, reimbursement of recruiting expenses for licensed physicians may constitute a reportable transfer of value under the federal transparency law commonly known as the Sunshine Act. Therefore, if you are a licensed physician who incurs recruiting expenses as a result of interviewing with Pfizer that we pay or reimburse, your name, address and the amount of payments made currently will be reported to the government. If you have questions regarding this matter, please do not hesitate to contact your Talent Acquisition representative.
EEO & Employment Eligibility
Pfizer is committed to equal opportunity in the terms and conditions of employment for all employees and job applicants without regard to race, color, religion, sex, sexual orientation, age, gender identity or gender expression, national origin, disability or veteran status. Pfizer also complies with all applicable national, state and local laws governing nondiscrimination in employment as well as work authorization and employment eligibility verification requirements of the Immigration and Nationality Act and IRCA. Pfizer is an E-Verify employer. This position requires permanent work authorization in the United States.
Pfizer endeavors to make www.pfizer.com/careers accessible to all users. If you would like to contact us regarding the accessibility of our website or need assistance completing the application process and/or interviewing, please email disabilityrecruitment@pfizer.com. This is to be used solely for accommodation requests with respect to the accessibility of our website, online application process and/or interviewing. Requests for any other reason will not be returned.
To learn more about acceptable and prohibited uses of AI during the recruitment process, please review our candidate AI-use guidelines available on Pfizer Careers.
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About Pfizer

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All over the world, Pfizer colleagues work together to positively impact health for everyone, everywhere. Our colleagues have the opportunity to grow and develop a career that offers both individual and company success; be part of an ownership culture that values diversity and where all colleagues are energized and engaged; and the ability to impact the health and lives of millions of people. Pfizer, a global leader in the biopharmaceutical industry, is continuously seeking top talent who are inspired by our purpose to innovate to bring therapies to patients that significantly improve their lives. Our Health and Science System Specialists Team provides leadership across patient care settings in the complex Hospital, Health System, and Key Medical Group environment to bring value to our customers and patients in this dynamic ecosystem.

Industry

Pharmaceutical and medicine manufacturing

Company size

10,000+ Employees

Headquarters location

New York, NY, US

Year founded

1849