Experimentation Manager, CNBC & MS NOW

Versant•Englewood Cliffs, NJ

1d•Hybrid

About The Position

We’re looking for a strategic and data-driven Manager, Experimentation to lead and scale our A/B testing practice across brands, driving more rigorous, insight-led decision making. This role will own the experimentation roadmap, designing high-impact tests and ensuring a cohesive testing strategy where learnings build over time. You’ll partner closely with analytics, product, editorial, marketing, and engineering teams to define hypotheses, structure experiments with statistical rigor, and ensure tests are executed and interpreted correctly. By maintaining a centralized view of all experimentation and a robust learning library, you’ll help the organization avoid conflicting tests, accelerate insight generation, and translate results into clear, actionable recommendations that drive growth and performance.

Requirements

5+ years of experience in experimentation, product analytics, or a related quantitative field
Strong foundation in statistics, including hypothesis testing, experimental design, and causal inference
Hands-on experience designing and analyzing A/B tests, ideally using tools such as Amplitude or similar experimentation platforms
Proven ability to translate business problems into structured experiments and actionable insights
Expertise in languages such as SQL, Python/R and experience with tools such as Databricks/Snowflake, Adobe/Google Analytics, Amplitude, Tableau/Looker/Omni, and experimentation platforms
Experience working cross-functionally with product, marketing, editorial, and engineering teams
Strong communication skills, with the ability to clearly explain methodology, results, and trade-offs to both technical and non-technical stakeholders
Ability to manage multiple concurrent experiments and prioritize effectively in a fast-paced environment
Passion for building scalable processes and fostering a culture of experimentation

Responsibilities

Define and prioritize a portfolio of high-impact tests aligned to business goals across product, editorial, marketing, and growth
Partner with cross-functional teams to translate business questions into clear, testable hypotheses
Design experiments end-to-end, including success metrics, test structure, segmentation, and measurement approach
Create a structured repository of experiment results, insights, and recommendations
Synthesize findings across tests to identify broader patterns and opportunities
Establish best practices for experiment design, execution, and analysis
Collaborate with analytics, product, editorial, marketing, and engineering teams to embed experimentation into key workflows