Data Scientist – Ecommerce & Mobile Analytics Focus - Fully Remote - USA

Morgan Mace; United States; Remote; USD 120,000 - 220,000; Full time

Job summary

A fast-growing digital platform is seeking a Data Scientist focused on ecommerce and mobile analytics. This remote role involves optimizing performance through analytics, driving strategic insights, and collaborating with engineering teams for data integration, thereby maximizing customer value and retention.

Benefits

Medical insurance

401(k)

Qualifications

• 3+ years in a Data Scientist role.
• Proficient in Python or R for statistical analysis.
• Experience with Google Analytics and machine learning.

Responsibilities

• Analyze customer purchase behaviors and reduce cart abandonment.
• Build predictive models for LTV and churn.
• Develop dashboards for key KPIs across departments.

Skills

Data Science

Machine Learning

Statistical Analysis

Ecommerce Analytics

A/B Testing

Dashboard Visualization

Education

Master’s degree in Data Science

Tools

Python

R

Tableau

Looker

Google Analytics

AWS

Job description

Data Scientist – Ecommerce & Mobile Analytics Focus - Fully Remote - USA

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Morgan Mace provided pay range

This range is provided by Morgan Mace. Your actual pay will be based on your skills and experience — talk with your recruiter to learn more.

Base pay range

$120,000.00/yr - $220,000.00/yr

About Our Client

Our client is a fast-growing, solutions-based digital platform serving a passionate and engaged audience through subscription-based digital products, mobile applications, and physical goods. With a focus on customer outcomes and cutting-edge technology, they deliver high-impact content, personalized tools, and innovative experiences to help users reach their goals. Their growing user base spans across the globe, and their platform continues to expand across ecommerce, mobile, and digital marketing channels.

Position Overview

We’re seeking a data-driven Data Scientist to help optimize ecommerce performance, improve mobile app experiences, and enhance marketing ROI across a high-growth, multi-channel platform. This role is critical in driving strategic insights across business units, maximizing customer retention and lifetime value, and owning data infrastructure from ingestion to insight. You’ll collaborate closely with engineering and product teams to ensure seamless data integration and unlock scalable growth.

Key Responsibilities

Ecommerce Analytics & Optimization

• Analyze customer purchase behaviors across digital and physical product lines
• Identify conversion opportunities and reduce cart abandonment
• Build predictive models for LTV, churn, and customer behavior
• Develop personalized product recommendations using machine learning
• Monitor and improve subscription retention through actionable insights
• Track and interpret iOS/Android app usage and behavioral data
• Improve feature adoption and app engagement metrics
• Partner with product to support feature testing and experimentation

Marketing & Ad Platform Analytics

• Build and refine attribution models across Facebook, Google, YouTube, and more
• Optimize CAC and ROAS using data-driven targeting and segmentation
• Forecast campaign performance and inform media budget strategy
• Deliver creative insights and audience performance recommendations

Business Intelligence & Reporting

• Develop dashboards and reports for key KPIs across departments
• Conduct cohort analysis and user journey mapping
• Surface actionable growth opportunities from data trends
• Provide analytical support for high-level strategic initiatives
• Manage and optimize a scalable data lake and warehouse ecosystem
• Design and maintain ETL/ELT pipelines for cross-platform data ingestion
• Ensure high-quality, secure, and well-governed data architecture
• Collaborate with engineering to embed analytics within product systems
• Document and enforce data modeling best practices

Required Qualifications

Technical Skills

• 3+ years in a Data Scientist role within ecommerce or digital-first environments
• Proficient in Python or R for statistical analysis and machine learning
• Experience with Google Analytics, Mixpanel, or Amplitude
• Solid understanding of A/B testing principles and statistical significance
• Skilled in dashboard and visualization tools (Looker, Tableau, Power BI)

Data Infrastructure Skills

• Experience with cloud data platforms (AWS, GCP, or Azure)
• Proficiency with Snowflake, BigQuery, or Redshift
• Familiarity with data lakes (S3, Delta Lake, etc.)
• ETL/ELT experience using Airflow, dbt, Fivetran or similar tools
• Strong knowledge of data modeling techniques
• Version control experience (Git); familiarity with CI/CD workflows

Domain Knowledge

• Ecommerce: Conversion, funnel, and subscription analytics
• Mobile Apps: In-app behavior, retention, and engagement metrics
• Digital Marketing: Attribution models, ROAS analysis, and campaign optimization
• Paid Media Platforms: Experience with Google Ads, Meta Ads, etc.
• Proven ability to build and deploy predictive models
• Knowledge of personalization algorithms and recommendation engines
• Experience with customer segmentation and time-series forecasting
• Expertise in cohort and behavioral analytics

Preferred Qualifications

• Master’s degree in Data Science, Statistics, Computer Science, or related field
• Background in subscription business models or mobile consumer products
• Interest in sports, performance tracking, or coaching analytics
• Experience with CDP/CRM platforms like Segment or Braze
• Exposure to streaming data (Kafka, Kinesis) and data APIs
• Familiarity with computer vision or image recognition

This role is managed in partnership with Morgan Mace, a trusted executive search partner. Our client is proud to be an equal opportunity employer and is committed to fostering a diverse and inclusive workplace. They do not discriminate on the basis of race, religion, color, national origin, gender, gender identity or expression, sexual orientation, age, disability status, or any other characteristic protected by law. All qualified applicants are encouraged to apply.

Seniority level

• Seniority level

  Not Applicable

Employment type

• Employment type

  Full-time

Job function

• Job function

  Research, Analyst, and Science

• Industries

  Sporting Goods Manufacturing, Spectator Sports, and Marketing Services

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Inferred from the description for this job

Medical insurance

401(k)

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