About Careertakes

👉 Important disclosure: Careertakes is a third-party recruiting platform supporting this hiring process. If selected, you will be employed directly by our client, Consumer Services — eCommerce & floral retail.

Applicants for this role may also receive access to additional matched opportunities through the Careertakes platform.

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What You’ll Do

You will build, validate, and maintain predictive models and analytics that drive acquisition, retention, and revenue decisions for the business. You will work closely with Marketing, Finance, Product, and Data Engineering to convert data into actionable insights and deploy models that inform strategy.

• Independently design, build, validate, and maintain predictive Customer Lifetime Value (LTV/CLV) models using transaction and behavioral datasets
• Develop statistical and machine learning models to forecast eCommerce revenue, orders, conversion rates, and average order value (AOV)
• Perform cohort analysis and customer segmentation to reveal trends in purchase behavior and lifetime value
• Build scenario models to evaluate growth opportunities, risks, and ROI of marketing investments
• Analyze historical trends, seasonality, and marketing performance to identify key drivers of business performance
• Collaborate with Data Engineering to ensure data quality, accessibility, and scalable analytical workflows
• Communicate model assumptions, performance, and recommendations to cross-functional stakeholders (Marketing, Finance, Product)
• Explore and pilot AI / Large Language Model (LLM) applications that can improve analytics, reporting, or business workflows

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Qualifications

• 3+ years of hands-on experience in data science and predictive modeling supporting eCommerce, direct-to-consumer (DTC), subscription, or digital consumer business
• Proven experience designing, building, and validating predictive Customer Lifetime Value (LTV/CLV) models with transaction and behavioral data
• Strong experience developing statistical and machine learning models for forecasting revenue, purchase frequency, and retention
• Advanced proficiency in Python and SQL; experience with customer-level datasets and model development workflows
• Strong understanding of model validation, performance evaluation, and continuous improvement
• Experience conducting cohort analysis and customer segmentation
• Ability to translate analytical outcomes into clear, actionable recommendations for business teams
• Master’s degree in Data Science, Statistics, or a related quantitative field — or equivalent practical experience

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Preferred Qualifications

• Experience with Google Cloud Platform (GCP) and BigQuery
• Experience deploying predictive models into production environments
• Familiarity with AI, LLMs, or generative AI applications and interest in developing AI-powered analytics solutions

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Compensation & Benefits

• Pay Range: $100,000 – $135,000 (final compensation dependent on skills & experience)
• Remote-eligible role (role is based in Minneapolis, MN and eligible for remote work)
• Typical benefits include medical, vision, dental, 401(k) match, virtual mental health resources, wellness incentives, and learning & development programs

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About Our Client

Confidential Client is a leader in consumer services and eCommerce within the floral/retail space. The organization focuses on delivering high-quality customer experiences and uses data to optimize acquisition, retention, and lifetime value. As a Careertakes candidate, you will be considered directly by the hiring organization.

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Equal Opportunity & Hiring Transparency

Careertakes and our client are Equal Opportunity Employers committed to building a diverse and inclusive workforce. We prohibit discrimination or harassment of any kind. To support a fair and efficient hiring process, AI tools may be used to assist with application review or resume screening. These tools do not replace human decision-making. Final hiring decisions are made by people.

If you have questions about how your data is used, please contact us directly.