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Accounting, Tax, Advisory, Professional Services

Data Scientist

United StatesRemoteFull Time$140,000–$150,000 /yrPosted 2 months ago

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Role summary

Moore is seeking a self-directed Data Scientist to independently define, scope, and execute analytical and modeling initiatives. This role focuses on developing reusable predictive models, analytical frameworks, and data products for operationalization across the enterprise. The Data Scientist will translate business needs into data-driven solutions, working with minimal oversight. Responsibilities include project ownership from concept to delivery, advanced statistical analysis, feature engineering, and collaborating with engineering and data teams to deploy models. The ideal candidate has a Bachelor's degree in a quantitative field, 3+ years of experience in data science, and proficiency in SQL and Python.

The Data Scientist is a highly self-directed individual contributor responsible for independently defining, scoping, and executing analytical and modeling initiatives from concept through delivery. This role focuses on developing predictive models, analytical frameworks, and new data products that can be operationalized and reused across the enterprise. The Data Scientist works with minimal day-to-day oversight and partners cross-functionally to translate ambiguous business problems into durable, data-driven solutions.

This is a full-time, salaried, US-based remote position.

Moore is a data-driven constituent experience management (CXM) company achieving accelerated growth for clients through integrated supporter experiences across all platforms, channels and devices. We are an innovation-led company that is the largest marketing, data and fundraising company in North America serving the purpose-driven industry with clients across education, association, political and commercial sectors.

Check out www.WeAreMoore.com for more information.

Your Impact:

Project Definition & Ownership

  • Independently identify, frame, and scope analysis and modeling opportunities based on business needs and data availability
  • Translate loosely defined questions into clear analytical objectives, success criteria, and deliverables
  • Own projects end-to-end, from initial exploration through validation, documentation, and delivery

Modeling & Advanced Analytics

  • Design, develop, and maintain predictive models using machine-learning algorithms
  • Perform advanced statistical analysis and feature engineering on large, multi-source datasets
  • Evaluate model performance, stability, and limitations, and iterate as needed

Data Product Development

Develop reusable analytical assets, scoring systems, features, and model outputs that function as data products

Partner with engineering and data teams to operationalize models and analytical outputs in production environments

Ensure analytical work is designed for scalability, repeatability, and long-term use

Collaboration & Communication

Work cross-functionally with analytics, engineering, product, and business stakeholders to align solutions with business goals

Clearly communicate analytical approaches, tradeoffs, and results to both technical and non-technical audiences

Provide analytical leadership and direction without requiring detailed instruction

Documentation & Standards

Document methodologies, assumptions, data transformations, and limitations to support transparency and reuse

Contribute to the evolution of data science standards, tooling, and best practices

What Success Looks Like:

By 6–12 months, a successful Data Scientist in this role will have:

Independently defined and delivered multiple analytical or modeling initiatives with minimal oversight

Developed at least one new reusable data product (e.g., model, scoring framework, feature set, or analytical asset) that is actively used by downstream teams or systems

Demonstrated strong judgment in scoping work appropriately, balancing rigor, speed, and business impact

Built credibility with cross-functional partners as a trusted analytical thought partner

Established clear, well-documented analytical patterns that others can understand, reuse, and extend

Proactively identified opportunities to improve existing models, data assets, or analytical workflows

Success in this role is measured by the ability to drive analytical work forward independently, not by waiting for detailed task definition.

Your Profile:

Bachelor’s degree in Computer Science, Statistics, Mathematics, or a related quantitative field required

Master’s degree preferred

3+ years of experience in data science, advanced analytics, or predictive modeling

3+ years of experience working with SQL and relational database systems

Experience developing reusable analytical or modeling assets strongly preferred

Experience in data-driven marketing, fundraising, or customer analytics a plus

Proven ability to operate independently in ambiguous problem spaces

Strong background in statistical modeling, predictive analytics, and feature engineering

Advanced SQL skills for data exploration, validation, and analysis

Proficiency in Python (and/or R) for modeling and analysis

Strong analytical judgment and problem-solving skills

Ability to clearly communicate complex analytical concepts

Excellent organizational skills and attention to detail

How We’ll Support You:

Join the largest marketing and fundraising company in North America serving the nonprofit industry where we prioritize innovation and professional growth.

Collaborate with industry subject matter experts with over 5,000 employees across the enterprise.

To help you stay energized, engaged and inspired, we offer a wide range of benefits including comprehensive healthcare, paid holidays and generous paid time off so you can have the time and space to recharge and pursue your other passions and be with the people you care about.

Moore is committed to creating a diverse environment and is proud to be an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status.

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