# Principal Data Scientist
## About the Role
Extuitive, a Flagship Pioneering–backed startup based in Cambridge, MA, is reimagining product innovation and go-to-market planning for the agentic age. We are seeking a **Principal Data Scientist** to provide technical leadership across the full lifecycle of data science and machine learning systems that predict and optimize advertising performance across channels.
In this role, you will define learning problems, training data, targets, and business outcomes; develop and rigorously validate predictive models; and translate model outputs into customer-facing decisions and measurable business value. You will work across paid social, search, display, video, and emerging advertising channels, partnering closely with data, product, engineering, and customer-facing teams in a fast-moving environment.
## Key Responsibilities
- Define learning targets and model advertising performance by identifying customer decisions and business interventions to influence.
- Construct training labels and measurement windows while assessing data quality, bias, and leakage.
- Develop predictive models for campaign and creative performance across channels, audiences, placements, and objectives.
- Build cross-channel measurement and optimization methods across paid social, search, display, video, and other advertising channels.
- Account for differences in measurement, attribution, and data availability across advertising platforms.
- Design and analyze experiments, incrementality tests, and causal inference approaches to validate business impact.
- Distinguish correlation from true business impact and ensure optimized targets translate into meaningful outcomes.
- Translate model outputs into clear, customer-facing recommendations for campaign strategy, budget allocation, targeting, creative selection, and optimization.
- Establish modeling and validation best practices covering forecasting, experimentation, feature engineering, model selection, and production data science.
- Design holdouts and backtests and evaluate calibration, uncertainty, failure modes, data drift, and decision thresholds before production or customer exposure.
- Own the model lifecycle across data, product, engineering, and customer discovery teams.
- Help move models from research and experimentation through deployment and customer validation.
- Support quantitative analysis required to successfully take data science systems to market.
## Required Qualifications
- **8+ years** of experience in data science, machine learning, statistics, or a related quantitative field.
- Advanced degree in Statistics, Mathematics, Economics, or another quantitative field, **or equivalent practical experience**.
- Strong expertise in **Python and SQL** and modern data science and machine learning frameworks.
- Strong foundation in **statistics, machine learning, experimental design, forecasting, and model evaluation**.
- Demonstrated experience 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 clearly explain assumptions, evidence, trade-offs, uncertainty, and validation results to technical and non-technical stakeholders.
- Ability to work effectively in a fast-paced, evolving environment with minimal oversight.
## Preferred Qualifications
- 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 making trade-offs between modeling sophistication, speed, interpretability, and business impact in ambiguous environments.
## Skills & Competencies
- Data science and machine learning
- Python and SQL
- Statistical modeling and analysis
- Experimental design and causal inference
- Forecasting and predictive modeling
- Model evaluation and validation
- Advertising and marketing analytics
- Cross-channel measurement and optimization
- Data quality, bias, leakage, and drift analysis
- Feature engineering and model selection
- Production data science and model lifecycle management
- Scientific and technical communication
- Customer-focused problem solving
- Cross-functional collaboration
- Decision-making in ambiguous, fast-paced environments
## Education & Experience
**Education:**
- Advanced degree in Statistics, Mathematics, Economics, or another quantitative field, or equivalent practical experience.
**Experience:**
- 8+ years of professional experience in data science, machine learning, statistics, or a related quantitative discipline.
- Demonstrated experience taking models through research, experimentation, production deployment, customer validation, and measurable business impact.
- Relevant experience with advertising, marketing, consumer, or marketplace performance data.
## Work Arrangement & Schedule
- **Location:** Cambridge, Massachusetts, United States
- **Work arrangement:** Onsite
- The original job description does not specify employment type, weekly hours, required schedule flexibility, or weekend requirements.
## Compensation & Benefits
- **Salary range:** $179,000–$236,500
- Compensation depends on factors including qualifications, skills, competencies, and experience.
- Healthcare coverage
- Annual incentive program
- Retirement benefits
- Other benefits
## Compliance / Additional Information
### About Flagship Pioneering
Flagship Pioneering invents and builds platform companies with the potential to create products that transform human health, sustainability, and beyond. Since its launch in 2000, Flagship has originated more than 100 companies addressing major challenges including human health, disease, agriculture, and sustainability.
### Equal Opportunity Employer
Flagship Pioneering is an equal opportunity employer. All qualified applicants will be considered without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, protected veteran status, or any other characteristic protected by law.
Flagship recognizes that strong candidates may bring unique strengths without meeting every qualification and is committed to building diverse and inclusive teams.
### Recruitment & Staffing Agencies
Flagship Pioneering and its affiliated Flagship Lab companies do not accept unsolicited resumes from recruitment or staffing agencies unless contacted directly by Flagship Pioneering’s internal Talent Acquisition team. Unsolicited submissions without a signed agreement will not result in referral or other fees.