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Senior Data Scientist

Role overview

Qualifications

  • 5+ years of experience in data science, machine learning, or quantitative analytics
  • Strong background in sales forecasting, revenue analytics, or time-series modeling
  • Advanced proficiency in Python or R for data analysis and machine learning workflows
  • Strong SQL expertise for analytical and modeling use cases

Responsibilities

  • Build and improve sales forecasting models across multiple product lines and geographic regions
  • Develop statistical and machine learning solutions for short-term and long-term revenue forecasting
  • Own the full machine learning lifecycle including feature engineering, training, deployment, monitoring, and explainability
  • Create self-service forecasting tools that enable real-time decision-making across business teams

Hard skills

Other skills

  • Communication
  • Mentorship
  • Teamwork
  • Decision Making

About the company

Recruiting from Scratch logo

Recruiting from Scratch

  • Staffing & Recruiting
  • Small startup
  • 11–50
Recruiting from Scratch provides recruiting services for companies that need to hire the best talent.

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Job description

Senior Data Scientist

Location: Remote – United States
Company Stage: Established EdTech / Growth-Stage Education Technology
Office Type: Remote
Salary: $110K – $150K Base + Bonus

Company Description

This education technology company is building next-generation curriculum, assessment, and learning platforms used by millions of students and educators across the United States. Their products combine learning science, analytics, and technology to help teachers personalize instruction and improve student outcomes at scale. The company operates across literacy, math, and science education while investing heavily in data infrastructure and predictive analytics capabilities.

What You Will Do

  • Build and improve sales forecasting models across multiple product lines and geographic regions
  • Develop statistical and machine learning solutions for short-term and long-term revenue forecasting
  • Own the full machine learning lifecycle including feature engineering, training, deployment, monitoring, and explainability
  • Create self-service forecasting tools that enable real-time decision-making across business teams
  • Translate model outputs into actionable business recommendations and strategic insights
  • Partner cross-functionally with analytics engineers, analysts, and business stakeholders
  • Mentor junior data scientists and contribute to technical standards, reviews, and team best practices
  • Influence forecasting strategy and drive data-informed planning across the organization

Ideal Background

  • 5+ years of experience in data science, machine learning, or quantitative analytics
  • Strong background in sales forecasting, revenue analytics, or time-series modeling
  • Expertise with forecasting methodologies such as ARIMA, Prophet, LSTM, or related approaches
  • Advanced proficiency in Python or R for data analysis and machine learning workflows
  • Strong SQL expertise for analytical and modeling use cases
  • Experience training and evaluating machine learning models using frameworks such as PyTorch, scikit-learn, xGBoost, or equivalent
  • Proven experience deploying machine learning systems into production environments such as AWS SageMaker, Databricks, or Snowflake
  • Strong understanding of software engineering best practices including version control and testing
  • Excellent communication skills with the ability to explain technical concepts to non-technical stakeholders
  • Comfortable operating independently in highly cross-functional environments

Preferred

  • Experience with Snowflake
  • Familiarity with Docker and Kubernetes
  • Experience within education technology or education-focused organizations
  • Prior experience building forecasting systems at scale across multiple business units or markets

Compensation and Benefits

  • Base salary: $110K – $150K
  • Annual discretionary bonus eligibility
  • Comprehensive medical, dental, and vision coverage
  • 401(k) retirement plan
  • Mental health and wellness benefits
  • Paid time off and parental leave
  • Professional development and learning programs
  • Fully remote work environment within the United States

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