Marketing Data Science Director

Job Description

Job Tittle: Marketing Data Science Director

Employment Type: On-Site/ Full-Time

Location: New York City, Metro Area

Reports To: Chief Marketing Officer (CMO)

Travel: Some travel required

The Opportunity

SmartEnergy is seeking a Director of Marketing Data Science to help drive the performance and profitability of our customer acquisition programs across Digital Marketing and Direct Mail .

Reporting directly to the Chief Marketing Officer , this is a senior, hands-on technical role within the Marketing organization . The ideal candidate combines deep expertise in data science, predictive modeling, marketing analytics, and MarTech with a strong understanding of customer acquisition and marketing economics.

This is not a Business Intelligence (BI) or reporting position. While the role will use data visualization and reporting tools, its primary focus is applying data science, statistical modeling, machine learning, experimentation, and advanced analytics to improve marketing decisions and business outcomes.

What You'll Do

• Build predictive models for response, conversion, customer acquisition, churn/retention, LTV, and customer profitability .
• Optimize Direct Mail targeting, list selection, segmentation, suppression, test/control strategies, and response modeling.
• Analyze and optimize Digital Marketing performance across paid search, social, display, affiliate, and other acquisition channels.
• Develop customer and prospect segmentation, propensity, scoring, and look-alike models .
• Design and evaluate A/B tests and multivariate experiments across audiences, offers, creative, pricing, landing pages, and enrollment flows.
• Develop and improve attribution and incrementality measurement to understand the true impact of marketing investments.
• Connect acquisition cost with customer margin, retention, churn, and LTV to optimize for profitable customer growth.
• Leverage first-party customer data, behavioral data, CDPs, MarTech, AI, and machine learning to improve targeting and marketing effectiveness.
• Leverage modern AI and generative AI tools to accelerate data analysis, model development, experimentation, automation, and the identification of actionable marketing insights.
• Partner with Marketing, Data Analytics, Technology, and senior leadership to turn complex analysis into clear, actionable business recommendations.

What We're Looking For

• 10+ years of experience in Data Science, Marketing Science, Advanced Analytics, Marketing Analytics, MarTech, or related fields.
• Bachelor's degree in Data Science, CIS, Computer Science, Statistics, Mathematics, Marketing, Business, or a related discipline .
• MBA, MS, or other relevant advanced degree preferred .
• Advanced hands-on expertise in SQL and working with large, complex datasets.
• Strong proficiency in Python and/or R .
• Demonstrated experience developing predictive and machine-learning models .
• Strong knowledge of statistical modeling, experimentation, segmentation, and A/B testing.
• Strong understanding of CAC/CPA, LTV, conversion, churn/retention, ROAS, cohort analysis, and marketing profitability .
• Experience with Digital Marketing analytics ; Direct Mail or direct-response analytics experience strongly preferred.
• Experience with CDPs, MarTech platforms, first-party customer data, and digital behavioral data .
• Experience with Tableau, Power BI, or similar visualization platforms.
• Strong communication skills and the ability to translate sophisticated analytical findings into recommendations for Marketing and senior business leaders.
• A hands-on mindset with the ability to independently take a business problem from data exploration through modeling, recommendation, and implementation.

This position is based in the New York City metropolitan area and requires in-office work five days per week . This is not a remote or hybrid position. Some business travel is required.

If you are a technically strong data scientist who also understands marketing and wants your work to directly influence who we acquire, how we acquire them, what we spend, and the long-term value those customers generate , we would like to hear from you.