Senior Data Scientist
About The Position
Prodege: A cutting-edge marketing and consumer insights platform, Prodege has charted a course of innovation in the evolving technology landscape by helping leading brands, marketers, and agencies uncover the answers to their business questions, acquire new customers, increase revenue, and drive brand loyalty & product adoption. Bolstered by a major investment by Blackstone in Q1 2026, Prodege looks forward to more growth and innovation to empower our partners to gather meaningful, rich insights and better market to their target audiences. Strategic Imperative: The Sr. Data Scientist is responsible for producing actionable insights to drive decision-making across the business through rigorous analysis, experimentation, and business-focused data science. This role applies statistical methods, ML modeling, and behavioral analysis to quantify user behavior, optimize lifecycle marketing, evaluate product and monetization strategies, and inform business decisions. The role will closely collaborate with business stakeholders to translate business problems and data into solutions. This position is centered on hands-on analytics, experimentation, and business impact. While the role will involve building predictive models, it is not focused on the deployment of live production models or ML Ops. The role is intended to incorporate AI agents to continuously improve and automate analytical processes As an organization, we go the extra mile to “Create Rewarding Moments” every day for our partners, consumers, and team. Come join us today!
Requirements
- Bachelor’s or Master’s degree in Statistics, Economics, Data Science, Mathematics, or a related quantitative field.
- Five or more (5+) years experience in data science roles.
- Robust experience in statistical analysis and experimental design, including hypothesis testing and causal reasoning.
- Understanding of frequentist and Bayesian statistical inference (e.g., PyMC) and demonstrated experience with A/B testing and experimentation frameworks.
- Experience leading the analysis and optimization of lifecycle marketing performance across the user journey.
- Fluency in SQL and ability to work with large, event-level datasets in data warehouse environments (e.g., Snowflake, BigQuery, Redshift).
- Fluency in Python/R (pandas, matplotlib/seaborn, tidyverse, or similar) and robust experience with common ML packages (scikit-learn or similar).
- Ability to develop 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.
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)
Responsibilities
- Drive data-informed progress across priority business areas by delivering rigorous analysis, actionable insights, and close partnership on optimization initiatives.
- Develop and operationalize user-level insights, segmentation frameworks, and behavioral analysis that enable smarter targeting, personalization, and lifecycle engagement across growth and marketing programs.
- Enable confident decision-making through statistically sound experimentation, structured insight generation, and systematic documentation of learnings to inform business planning, long-term strategy, and continuous improvement.
- Act as a strategic thought partner with stakeholders by enacting methodical business analysis and offering proactive diagnostics, observations, and recommendations.
- Build and maintain customer segmentation, propensity, and scoring mechanisms for use in lifecycle marketing
- Partner with marketing to devise and execute on policies and experimentation frameworks
- Partner with Revenue Operations team 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.
- Define and evangelize best practices and frameworks for design and measurement to ensure statistical rigor
- Partner on A/B tests across product, marketing, and monetization initiatives, owning 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.
- Partner with Analytics Engineering to define canonical and semantic models and other business data requirements necessary to support a well functioning Data Science discipline.
- 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 workflows and recurring analytical patterns into agentic analytics systems that scale insight generation.
Benefits
- medical
- dental
- vision
- STD
- LTD
- basic life insurance
- flexible PTO
- paid sick leave
- eight paid holidays
- option to purchase shares of Company stock commensurate with their position, which vests over four years
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What This Job Offers
Job Type
Full-time
Career Level
Senior
