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Meta Data Scientist Jobs in Boston, MA (NOW HIRING)

Meta Product Managers work with cross-functional teams of engineers, designers, data scientists and researchers to build products. We are looking for Pr...

Own infrastructure capacity planning for Meta: including Servers, Data Centers, Network * Design ... Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or ...

Product Manager

Boston, MA ยท On-site

$173K/yr

Meta Product Managers work with cross-functional teams of engineers, designers, data scientists and researchers to build products. We are looking for Product Managers who value moving quickly.

Lab Data Manager

Cambridge, MA ยท On-site

$119K - $199K/yr

... scientific data management solutions for R&D * Contributes to designing/defining solutions to make lab data secure & ready for reuse through (meta)data standard format, storage and archiving ...

Lab Data Manager

Cambridge, MA ยท On-site

$119K - $199K/yr

... scientific data management solutions for R&D * Contributes to designing/defining solutions to make lab data secure & ready for reuse through (meta)data standard format, storage and archiving ...

As a Competitive Intelligence Lead in Meta's Competitive Intelligence organization, you will operate at the intersection of advanced analytics, data science, and market strategy. You will lead major ...

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Meta Data Scientist information

See Boston, MA salary details

$40.7K

$133.3K

$213.5K

How much do meta data scientist jobs pay per year?

As of Sep 8, 2026, the average yearly pay for meta data scientist in Boston, MA is $133,336.00, according to ZipRecruiter salary data. Most workers in this role earn between $107,000.00 and $147,700.00 per year, depending on experience, location, and employer.

What is a Meta Data Scientist?

A Meta Data Scientist at Meta (formerly Facebook) uses data analysis, machine learning, and statistical techniques to drive business decisions and improve products. They work with large-scale datasets to extract insights, optimize algorithms, and enhance user experiences. Responsibilities often include A/B testing, predictive modeling, and collaborating with engineers and product teams. The role requires strong programming skills (Python, SQL, R), expertise in statistical analysis, and experience with data visualization. Typically, candidates have backgrounds in computer science, mathematics, or related fields.

What are some typical projects or challenges a Meta Data Scientist might encounter on the job?

As a Meta Data Scientist, you may work on projects ranging from large-scale data infrastructure optimization to advanced predictive modeling and experimentation. Challenges often include handling massive and complex datasets, ensuring data quality, and translating business needs into data-driven solutions. You'll likely collaborate closely with engineers, product managers, and other scientists to deliver impactful insights and scalable tools. This dynamic environment encourages creative problem-solving and offers opportunities for skill advancement and cross-functional learning. The role frequently involves balancing technical execution with clear communication to stakeholders.

What are the key skills and qualifications needed to thrive in the Meta Data Scientist position, and why are they important?

To thrive as a Meta Data Scientist, you need a strong background in statistics, machine learning, data analytics, and computer science, often supported by an advanced degree in a relevant field. Familiarity with programming languages like Python or R, cloud computing platforms, big data tools such as Spark or Hadoop, and certifications in data science or analytics are highly valuable. Strong collaborative, problem-solving, and communication skills help foster insights and share results effectively across multidisciplinary teams. These skills are essential for building scalable models, generating actionable data-driven insights, and effectively contributing to organizational innovation.

How much do meta data scientists make?

Meta Data Scientists typically earn a median salary ranging from $100,000 to $150,000 annually, depending on experience, location, and education. Senior roles or those with specialized skills in machine learning and data engineering can earn higher compensation, often exceeding $180,000 per year.

How to get a data science job at Meta?

To get a data science job at Meta, candidates should have strong skills in statistics, programming (Python or R), and data analysis, along with experience in machine learning and data visualization. A relevant degree in a quantitative field and a solid portfolio of projects or prior work can improve chances. Familiarity with tools like SQL, Hadoop, or Spark and understanding of the company's products and data infrastructure are also beneficial.

What are the most commonly searched types of Meta Data Scientist jobs in Boston, MA?

The most popular types of Meta Data Scientist jobs in Boston, MA are:

What are popular job titles related to Meta Data Scientist jobs in Boston, MA?

For Meta Data Scientist jobs in Boston, MA, the most frequently searched job titles are:

What job categories do people searching Meta Data Scientist jobs in Boston, MA look for?

The top searched job categories for Meta Data Scientist jobs in Boston, MA are:

Infographic showing various Meta Data Scientist job openings in Boston, MA 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, with an average salary of $133,336 per year, or $64.1 per hour.

Principal Data Scientist

Flagship Pioneering, Inc.

Cambridge, MA โ€ข On-site

Full-time

Medical, Retirement

Posted 13 days ago


Key responsibilities

  • Define learning targets, construct training labels, assess data quality, and develop predictive models to forecast advertising performance across multiple channels.

  • Develop methods to compare and optimize advertising performance across channels while accounting for differences in measurement, attribution, and data availability.

  • Design and analyze experiments, incrementality tests, and causal inference approaches to verify the impact of optimized targets on business outcomes.


Job description

COMPANY DESCRIPTION
Extuitive is a Flagship Pioneering-backed startup reimagining product innovation for the AI era. Our mission is to revolutionize go to market for planning and execution for the agentic age. Based in Cambridge, MA, we operate like a special ops unit-fast-moving, data-driven, and relentlessly focused on impact.
THE ROLE
As a Principal Data Scientist, you'll be a technical leader responsible for the full lifecycle of the models and data science systems that predict and optimize advertising performance across channels. You'll define the learning problems, training data, targets, and business outcomes to influence; train and rigorously validate the right models offline; and take the technology to market through customer-facing validation. You'll work across paid social, search, display, video, and emerging channels, translating complex, noisy advertising data into robust models, explainable decisions, and measurable customer value as our platform and data scale.
KEY RESPONSIBILITIES
  • Define Learning Targets & Model Advertising Performance - Identify the customer decision and business intervention to influence; construct training labels and measurement windows; assess data quality, bias, and leakage; and develop predictive models that forecast campaign and creative performance across channels, audiences, placements, and objectives.
  • Build Cross-Channel Measurement & Optimization Systems - Develop methods to compare and optimize advertising performance across paid social, search, display, video, and other channels while accounting for differences in measurement, attribution, and data availability.
  • Develop Experimentation & Causal Measurement Approaches - Design and analyze experiments, incrementality tests, and causal inference approaches to verify that the targets we optimize change business outcomes, not just model metrics, and to distinguish correlation from true impact.
  • Translate Models into Marketable Decisions - Turn model outputs into clear, customer-facing recommendations for campaign strategy, budget allocation, targeting, creative selection, and optimization-decisions that can be explained, tested, and proven useful in market.
  • Advance Modeling & Validation Best Practices - Shape our approach to forecasting, experimentation, feature engineering, model selection, and production data science, including holdout and backtesting design, calibration, uncertainty, failure modes, data drift, and decision thresholds before production or customer exposure.
  • Own the Model Lifecycle Cross-Functionally - Partner across data, product, engineering, and customer discovery to move models from learning problem through deployment and customer validation, while supporting the quantitative work needed to make that lifecycle successful.

PROFESSIONAL EXPERIENCE & QUALIFICATIONS
  • 8+ years of data science, machine learning, statistics, or related quantitative experience.
  • Advanced degree in Statistics, Mathematics, Economics, or another quantitative field, or equivalent practical experience.
  • Strong expertise in Python, SQL, and modern data science and machine learning frameworks.
  • Strong foundation in statistics, machine learning, experimental design, forecasting, and model evaluation.
  • Demonstrated track record of taking models from research and experimentation through production deployment, customer validation, and measurable business impact.
  • Experience modeling advertising, marketing, consumer, or marketplace performance, including metrics such as conversion, engagement, acquisition, ROAS, CAC, or lifetime value.
  • Experience working with advertising data across multiple channels and platforms, including paid social, search, display, or video.
  • Experience with causal inference, incrementality testing, attribution, media mix modeling, or related approaches to measuring marketing effectiveness.
  • Exceptional scientific communication skills, with the ability to earn trust across technical and non-technical stakeholders by clearly explaining assumptions, evidence, trade-offs, uncertainty, and validation results.
  • Comfortable working in a fast-paced, evolving environment with minimal oversight.

Nice to Have
  • Experience building predictive advertising or marketing optimization products in an early-stage startup.
  • Deep familiarity with advertising platform data and APIs, including Meta, Google, TikTok, LinkedIn, or similar platforms.
  • Experience with budget optimization, bidding, recommendation systems, uplift modeling, or other decision-making systems.
  • Experience applying LLMs, embeddings, or other foundation models to advertising, creative, or consumer data.
  • Experience developing models in data-sparse or cold-start environments where historical performance data is limited.
  • Comfort with ambiguity and making trade-offs between modeling sophistication, speed, interpretability, and business impact.

ABOUT FLAGSHIP PIONEERING:
Flagship Pioneering invents and builds platform companies, each with the potential for multiple products that transform human health, sustainability and beyond. Since its launch in 2000, Flagship has originated more than 100 companies. Many of these companies have addressed humanity's most urgent challenges: vaccinating billions of people against COVID-19, curing intractable diseases, improving human health, preempting illness, and feeding the world by improving the resiliency and sustainability of agriculture.
Flagship has been recognized twice on FORTUNE's "Change the World" list, an annual ranking of companies that have made a positive social and environmental impact through activities that are part of their core business strategies and has been twice named to Fast Company's annual list of the World's Most Innovative Companies. Learn more about Flagship at www.flagshippioneering.com.
At Flagship, we accept impossible missions to enable bigger leaps. Our core values guide us through uncertainty and toward lasting impact.
We are an equal opportunity employer. All qualified applicants will be considered for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, protected veteran status, or any other characteristic protected by law.
We recognize that great candidates often bring unique strengths without fulfilling every qualification. If you have some of the experience listed above but not all, please apply anyway. We are dedicated to building diverse and inclusive teams and look forward to learning more about your background and interest in Flagship.
Recruitment & Staffing Agencies: Flagship Pioneering and its affiliated Flagship Lab companies (collectively, "FSP") do not accept unsolicited resumes from any source other than candidates. The submission of unsolicited resumes by recruitment or staffing agencies to FSP or its employees is strictly prohibited unless contacted directly by Flagship Pioneering's internal Talent Acquisition team. Any resume submitted by an agency in the absence of a signed agreement will automatically become the property of FSP, and FSP will not owe any referral or other fees with respect thereto.
Privacy Notice for Applicants: When you apply for a role at Flagship Pioneering or one of its portfolio companies, we collect and use personal information you provide (such as your name, contact details, work history, and application materials) to evaluate your application, communicate with you, and comply with legal obligations. Your application data is processed through Greenhouse, our applicant tracking system, and may also be reviewed using AI-assisted screening tools. We do not sell your personal information. California residents have rights under the CCPA/CPRA including to know, delete, and opt out of the sharing of their personal information. If you are located in the EU or UK, we process your data under GDPR and you have rights to access, rectify, and erase your data. To exercise your rights or for questions, contact privacy@flagshippioneering.com.
The salary range for this role is $179,000 - $236,500. Compensation for the role will depend on a number of factors, including a candidate's qualifications, skills, competencies, and experience. Extuitive, Inc. currently offers healthcare coverage, annual incentive program, retirement benefits and a broad range of other benefits. Compensation and benefits information is based on Extuitive, Inc.'s good faith estimate as of the date of publication and may be modified in the future.
Privacy Notice for Applicants: When you apply for a role at Flagship Pioneering or one of its portfolio companies, we collect and use personal information you provide (such as your name, contact details, work history, and application materials) to evaluate your application, communicate with you, and comply with legal obligations. Your application data is processed through Greenhouse, our applicant tracking system, and may also be reviewed using AI-assisted screening tools. We do not sell your personal information. California residents have rights under the CCPA/CPRA including to know, delete, and opt out of the sharing of their personal information. If you are located in the EU or UK, we process your data under GDPR and you have rights to access, rectify, and erase your data. To exercise your rights or for questions, contact privacy@flagshippioneering.com.