# Principal Data Scientist, GTM Data Science
## About the Company
SimpliSafe is a high-tech home security company focused on its mission of keeping every home secure. The company promotes a collaborative, innovative, and inclusive culture where employees can grow, take on meaningful challenges, and make an impact on customers.
## About the Role
As a **Principal Data Scientist, GTM Data Science**, you will report to the Senior Director of Data Science and serve as a senior technical leader across growth, marketing, customer lifecycle, and personalization.
You will shape data science strategy and production systems that help acquire, retain, and grow subscriber relationships while improving the customer experience. The role combines hands-on machine learning, marketing science, experimentation, causal inference, MLOps, and technical leadership.
## Key Responsibilities
* Lead technical strategy for growth, marketing, customer lifecycle, and personalization data science initiatives.
* Build and deploy production machine learning solutions that deliver measurable business outcomes.
* Develop models and decision systems for:
* Customer acquisition and conversion
* Customer retention
* Customer segmentation
* Personalization
* Customer lifetime value
* Next-best-action decisioning
* Apply experimentation, causal inference, incrementality measurement, and marketing effectiveness methodologies.
* Design scalable data and feature pipelines for production machine learning systems.
* Support model deployment, monitoring, and MLOps across distributed computing environments.
* Work with modern cloud data and machine learning platforms.
* Set technical direction, influence roadmaps, and drive execution across teams.
* Mentor other data scientists and technical team members.
* Communicate complex modeling concepts clearly to technical and non-technical stakeholders.
* Apply advanced machine learning and AI techniques to customer and go-to-market decision-making.
## Required Qualifications
* Typically **6+ years of experience** in data science, machine learning, applied statistics, or a related field, or equivalent demonstrated expertise.
* Deep expertise in **marketing science, customer personalization, lifecycle modeling, and applied machine learning**.
* Strong hands-on experience building and deploying production machine learning solutions with measurable business impact.
* Experience developing models and decision systems for customer acquisition, conversion, retention, segmentation, personalization, lifetime value, or next-best-action use cases.
* Strong understanding of **experimentation, causal inference, incrementality measurement, and marketing effectiveness**.
* Significant experience with **MLOps, model deployment, model monitoring, and distributed compute environments**.
* Proficiency with:
* Python
* SQL
* Databricks
* AWS SageMaker
* Spark
* MLflow
* Modern cloud data platforms
* Experience designing scalable data and feature pipelines for production ML systems.
* Ability to operate as a senior individual contributor while setting technical direction, influencing roadmaps, mentoring others, and driving execution.
* Strong communication and stakeholder management skills.
## Preferred Qualifications
* Hands-on experience with advanced machine learning techniques such as:
* Gradient Boosted Trees
* Neural networks
* Transformer-based models
* Experience applying modern AI/ML techniques involving unstructured data or advanced signal integration in production.
* Experience designing or deploying **agentic AI** solutions that orchestrate models, tools, data, and workflows to automate or augment GTM decision-making.
* Experience building recommendation, personalization, real-time decisioning, or next-best-action systems.
* Experience in subscription, ecommerce, smart home, security, telecommunications, insurance, fintech, or other customer lifecycle-driven businesses.
* Advanced degree in Computer Science, Statistics, Machine Learning, Economics, Applied Mathematics, Engineering, or another quantitative field.
## Technical Skills & Keywords
**Data Science:** Data Science, Applied Statistics, Marketing Science, Customer Analytics, Customer Lifecycle Modeling, Personalization, Segmentation, Customer Lifetime Value, Marketing Effectiveness
**Machine Learning:** Machine Learning, Applied Machine Learning, Gradient Boosted Trees, Neural Networks, Transformers, Recommendation Systems, Next-Best Action, Real-Time Decisioning
**AI & MLOps:** AI/ML, Agentic AI, MLOps, Model Deployment, Model Monitoring, MLflow, Feature Engineering, Production ML
**Data & Cloud:** Python, SQL, Databricks, AWS SageMaker, Spark, Cloud Data Platforms, Distributed Computing, Data Pipelines, Feature Pipelines
**Analytics & Experimentation:** Experimentation, Causal Inference, Incrementality, Customer Acquisition, Conversion, Retention, Growth Analytics
## Company Values
* **Customer Obsessed** — Putting customers at the center of decision-making and building strong relationships.
* **Aim High** — Continuously raising standards and pursuing ambitious goals.
* **No Ego** — Maintaining an open, inclusive, humble, and collaborative approach.
* **One Team** — Working collaboratively to achieve shared outcomes.
* **Lift As We Climb** — Supporting the growth and development of others.
* **Lean & Nimble** — Working efficiently and adapting quickly in an often ambiguous environment.
## Compensation & Benefits
The target annual base pay range is **$182,000–$242,600**. Individual compensation may vary based on job-related skills, experience, qualifications, work location, and other business factors.
The total rewards package may include:
* Health and wellness benefits
* Security and financial benefits
* Free SimpliSafe system and professional monitoring for your home
* Employee Resource Groups (ERGs)
* Additional total rewards offerings
## Work Location
**Boston, Massachusetts, United States — Onsite**
**Source listing discrepancy:** The listing metadata identifies **Socket.dev** as the employer, while the job description identifies **SimpliSafe** throughout. The description above preserves the employer information stated in the job description rather than inventing or combining company details.