Rockerbox empowers marketing executives to confidently make data-driven decisions, helping brands such as Tula, Figs, and Burton with the strategic decision-making that drives growth. To do so, Rockerbox offers a unique suite of product lines that centralize data and offer diversified measurement methodologies. The foundation of Rockerbox's solution is data centralization. Atop this foundation, the platform enables marketers to choose from a range of measurement methodologies, giving customers the flexibility to choose the most appropriate approach for their specific needs and questions.
As a Data Scientist at Rockerbox, you will take full ownership of testing methodologies and statistical experimentation, ensuring that marketers have precise insights into campaign effectiveness. This role involves developing and iterating on testing frameworks (planning through analysis), with a strong emphasis on adapting and refining the existing packages for our needs. If you enjoy designing rigorous experiments, optimizing statistical models, and working at the intersection of data science and product, this is the role for you.
Responsibilities
Own the end-to-end development of testing methodologies, ensuring statistical robustness.
Adapt, optimize, and iterate on the current testing packages, translating R-based methodologies into Python.
Design and implement statistical frameworks for campaign effectiveness measurement.
Work closely with engineering to integrate testing methodologies into the Rockerbox platform.
Conduct exploratory data analysis to refine test parameters and ensure accuracy.
Stay up to date with the latest causal inference and experimental design techniques.
Requirements
5+ years of experience in data science.
Strong knowledge of statistical testing, experimental design, and regression modeling.
Proficiency in Python (NumPy, Pandas, Statsmodels, etc.); experience adapting R-based packages is a plus.
Familiarity with marketing analytics concepts such as campaign allocation and budget optimization.
Ability to translate complex statistical methodologies into actionable insights.
Strong problem-solving skills and experience working cross-functionally with engineering and product teams.
Why You’ll Love Rockerbox: At Rockerbox, you’ll find a fast-paced, results-driven environment where your work has a direct impact on our growth and the success of our clients. Our iterative development process means you’ll see your contributions come to life quickly. You’ll join a supportive, light-hearted team that values collaboration and innovation. We are committed to professional growth and will actively support your development in both technical and business domains.
Skills Required
- 5+ years of industry experience with a BA or BSc in sciences or engineering or 2+ years of industry experience with a MSc or PhD degree
- Strong knowledge of regression modelling, statistical testing and experimental design
- Proficiency in scientific Python stack (NumPy, Pandas, Statsmodels, Matplotlib)
DoubleVerify Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about DoubleVerify and has not been reviewed or approved by DoubleVerify.
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Fair & Transparent Compensation — Salary ranges are posted for U.S. roles and annual pay‑equity analyses are conducted, signaling structured and transparent pay practices. Pay for many technical and product roles is considered competitive with clear bands visible on postings.
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Healthcare Strength — Health coverage is described as comprehensive, with medical, dental, vision, and global mental‑health resources. Wellness support includes designated mental wellness days and related activities.
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Leave & Time Off Breadth — Self‑directed (unlimited) PTO expands flexibility beyond standard accruals. Quarterly wellness or recharge days further reinforce planned time away.
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