Remote Staff Data Scientist

Motion Recruitment

Boston (MA)

Remote

USD 170,000 - 220,000

Full time

48 hours ago
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Benefits offered by this job

Medical Insurance
Dental Benefits
Vision Benefits
PTO
401(k)

Job summary

Motion Recruitment is seeking a Staff Data Scientist to build the data function from the ground up and lead cross-functional data initiatives. You will design pipelines, analytics frameworks, and experimentation practices to drive product decisions and business outcomes. The role requires strong Python/SQL skills, statistical expertise, and a track record of delivering enterprise-grade data solutions.

Qualifications

  • 7+ years in Data Science, Analytics, or Data Engineering.
  • Advanced Python and SQL proficiency.
  • Experience building analytics capabilities from ground up.
  • Strong statistics, experimentation, causal inference, and hypothesis testing.
  • Experience designing data pipelines and data models.
  • Ability to work with messy, incomplete datasets.
  • Translate business questions into analytical solutions.
  • Strong communication with stakeholders.
  • Autonomy and initiative with minimal oversight.
  • Graduate degree or equivalent experience in quantitative field.

Responsibilities

  • Design and build core analytics and data infrastructure.
  • Develop and maintain data pipelines, instrumentation, and reporting systems.
  • Collect, clean, transform, and model data from multiple sources.
  • Identify patterns in incomplete datasets and actionable signals.
  • Design and execute experiments to validate hypotheses.
  • Build dashboards, metrics frameworks, and decision-support tools.
  • Create scalable data science processes, standards, and docs.
  • Partner with Product, Engineering, and business teams to shape roadmap.
  • Communicate findings to executive stakeholders.
  • Serve as subject matter expert for rigor and best practices.

Skills

Python
SQL
Data analytics
Statistics
Experimentation
Communication
Independent initiative

Education

Graduate degree in Statistics / Data Science / CS / Economics / Math or related field

Tools

Data pipelines

Job description

Job Description A growing technology company is seeking a Staff Data Scientist to build and lead the foundation of its data science function. This is a highly visible, high-impact role for someone who thrives in ambiguity, enjoys solving difficult problems with imperfect information, and can bridge the gap between data engineering and data science.

You will be responsible for turning fragmented, incomplete, and evolving data into actionable business insights. As the organization's senior data expert, you will design the infrastructure, pipelines, analytics frameworks, and experimentation practices that drive product and business decisions.

This role is ideal for a builder who enjoys working in fast-paced environments where processes, datasets, and success metrics are still being defined. You'll partner closely with Product, Engineering, and business leaders to identify meaningful signals, validate hypotheses, and create a scalable data foundation for future growth.

Required Skills & Experience
  • 7+ years of experience in Data Science, Applied Science, Analytics Engineering, Data Engineering, or related fields
  • Advanced proficiency in Python and SQL
  • Experience building analytics and data science capabilities from the ground up
  • Strong understanding of statistics, experimentation, causal inference, and hypothesis testing
  • Experience designing and maintaining data pipelines and data models
  • Proven ability to work with small, messy, incomplete, or ambiguous datasets
  • Experience translating complex business questions into analytical solutions
  • Strong communication skills with the ability to influence technical and non-technical stakeholders
  • Experience operating independently and driving initiatives with minimal oversight
  • Graduate degree in Statistics, Data Science, Computer Science, Economics, Mathematics, or a related quantitative discipline, or equivalent industry experience
Desired Skills & Experience
  • Startup or early-stage product experience
  • Experience with product analytics and user behavior analysis
  • Familiarity with modern cloud data platforms and data warehouse technologies
  • Experience developing predictive models and machine learning solutions
  • Experience influencing product strategy through data-driven insights
  • Background in B2B SaaS, HR technology, behavioral science, or related industries
  • Experience leveraging AI tools to improve productivity and analytical processes
What You Will Be Doing Daily Responsibilities
  • Design and build the organization's core analytics and data infrastructure
  • Develop and maintain data pipelines, instrumentation, and reporting systems
  • Collect, clean, transform, and model data from multiple disparate sources
  • Identify patterns and opportunities within incomplete and noisy datasets
  • Design and execute experiments to evaluate product and business hypotheses
  • Build dashboards, metrics frameworks, and decision-support tools
  • Create scalable data science processes, standards, and documentation
  • Partner with Product, Engineering, and business teams to shape strategy and roadmap decisions
  • Communicate analytical findings and recommendations to executive stakeholders
  • Serve as the subject matter expert for statistical rigor, experimentation, and analytics best practices
Breakdown
  • 80% Hands-On Data Science & Analytics Engineering
  • 20% Strategic Partnership & Stakeholder Collaboration
The Offer
  • $170,000 - $220,000 Base Salary
  • Potential bonus and/or equity package
  • Flexible remote work options within the United States
  • Opportunity to build and own a data science function from the ground up
  • High visibility and direct impact on company strategy and product direction
You will receive the following benefits
  • Medical Insurance
  • Dental Benefits
  • Vision Benefits
  • Paid Time Off (PTO)
  • 401(k)

Applicants must be currently authorized to work in the US on a full-time basis now and in the future.

Posted By: Nick Ramler

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