Senior Data Scientist

Data Scientist

This is a hands-on, high-impact role, and it's a build-and-improve one, not a maintain-what-exists one. Prodege is moving fast and changing fast, and we need a data scientist who finds that energizing rather than exhausting.

If you want a settled analytics function with fixed metrics and a steady backlog, this isn't your role, and that's okay. But if you're the kind of scientist who walks into ambiguity and starts turning messy data into clear decisions, who'd rather define the frameworks than inherit them, and who's genuinely excited to bring AI agents into how analytics gets done, keep reading.

One thing to be clear about up front: this role is centered on hands-on analytics, experimentation, and business impact. You'll build predictive models, but this is not an ML Ops or live-production-model role. If you love the analysis, the experiment design, and the business decisions that follow, and you're happy to leave production model serving to others, you're in the right place.

What you'll do here:

You'll produce actionable insights that drive decisions across the business through rigorous analysis, experimentation, and business-focused data science. You'll apply statistical methods, ML modeling, and behavioral analysis to quantify user behavior, optimize lifecycle marketing, evaluate product and monetization strategies, and inform business decisions, working closely with stakeholders to translate business problems into solutions. And you'll help incorporate AI agents to continuously improve and automate analytical processes.

Analytical insights and modeling

• Act as a strategic thought partner to stakeholders through methodical business analysis and proactive diagnostics, observations, and recommendations
• Build and maintain customer segmentation, propensity, and scoring mechanisms for lifecycle marketing
• Partner with marketing to design and execute policies and experimentation frameworks
• Partner with Revenue Operations to streamline pricing and rewards decisions through automated statistical frameworks
• Communicate findings clearly and document learnings to build reusable knowledge
• Provide technical guidance and mentorship to more junior team members

Statistical rigor

• Define and evangelize best practices for design and measurement to ensure statistical rigor
• Own A/B tests across product, marketing, and monetization initiatives, including the statistical experimentation frameworks (Bayesian and frequentist) and tooling
• Partner with teams on hypotheses, success metrics, and post-test actions
• Own the capture and scaling of learnings to improve future experimentation

Data foundations support

• Partner with Analytics Engineering to define canonical and semantic models and the business data requirements a well-functioning Data Science discipline needs
• Enable reliable lifecycle tracking and feature generation
• Expose behavioral learnings to ML engineers to inform feature and model development
• Partner with AI teams to translate recurring analytical patterns into agentic analytics systems that scale insight generation

What success looks like:

Success is consistently translating data into clear, actionable decisions that improve product performance, lifecycle marketing effectiveness, and monetization outcomes. It shows up in well-designed experiments and frameworks that drive confident choices, insights that meaningfully influence strategy, and strong partnerships with Analytics Engineering and Machine Learning through precise data definitions and feature guidance. Over time, it's evident in a growing body of documented learnings, trusted metrics, and measurable impact on how the organization tests, learns, and optimizes.

Why this role is worth your time:

• Your analysis drives real decisions, on pricing, rewards, lifecycle marketing, and monetization, not dashboards nobody reads
• You own experimentation end to end, the frameworks, the tooling, the standards, both Bayesian and frequentist
• You'll help build agentic analytics, bringing AI agents into how the team works, which is still greenfield here
• Backed for growth: Prodege closed a major Blackstone investment in Q1 2026, which means real momentum and real investment in the function you'd be shaping

A bit about Prodege:

Prodege is a marketing and consumer insights platform that helps leading brands, marketers, and agencies answer their business questions, acquire customers, grow revenue, and build brand loyalty. We go the extra mile to "Create Rewarding Moments" for our partners, consumers, and team. We operate with startup speed and a startup appetite for change, backed by the resources of a major investment partner.

The must-haves:

• Bachelor's or Master's in Statistics, Economics, Data Science, Mathematics, or a related quantitative field
• 5+ years of experience in data science roles
• Strong experience in statistical analysis and experimental design, including hypothesis testing and causal reasoning
• Understanding of frequentist and Bayesian statistical inference (e.g., PyMC), with demonstrated A/B testing and experimentation experience
• Experience leading the analysis and optimization of lifecycle marketing performance across the user journey
• Fluency in SQL and comfort working with large, event-level datasets in data warehouse environments (Snowflake, BigQuery, Redshift, or similar)
• Fluency in Python/R (pandas, matplotlib/seaborn, tidyverse, or similar) and strong experience with common ML packages (scikit-learn or similar)
• Ability to build effective data visualizations that clearly communicate insights to business stakeholders
• Strong communication skills, with the ability to translate complex analysis into clear, actionable business insights
• Knowledge of agentic analytics workflows and best design practices
• High attention to data quality, metric definitions, and analytical rigor

The nice-to-haves:

• Experience in loyalty programs, performance marketing, or market research
• Deep learning experience
• Experience building interactive dashboards in modern BI platforms
• Experience building agentic analytics workflows
• Experience building data applications (e.g., Streamlit, Shiny)

Pay Transparency:

The anticipated base salary range for this position is $165,000 to $200,000. The final salary offered to a successful candidate will be dependent on several factors that may include, but are not limited to: the type and length of experience within the job, type and length of experience within the industry, the type and length of knowledge and skills for the position, education, training, etc. Prodege is a multi-state employer, and final compensation within this range could be impacted by work location. Please note that the compensation details listed in US role postings reflect the base salary only and do not include bonus, equity, or benefits.

Prodege Benefits:

Prodege offers a comprehensive benefits package to US full-time employees, including medical, dental, vision, short-term disability, long-term disability, and basic life insurance. Employees receive flexible PTO, plus paid sick leave prorated based on hire date, and eight paid holidays throughout the calendar year.

Equal Employment Opportunity Statement:

At Prodege, we are committed to creating a diverse and inclusive environment. We are proud to be an Equal Opportunity Employer and do not discriminate on the basis of race, color, religion, sex, sexual orientation, gender identity or expression, national origin, age, disability, veteran status, or any other characteristic protected by law. We encourage individuals of all backgrounds to apply.

FCIHO:

Employers will consider qualified applicants with criminal histories in a manner consistent with the requirements of FCIHO.