Rockerbox with DoubleVerify 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. To learn more, visit ;br>
As a Senior Data Scientist, you will take full ownership of statistical modeling, ensuring that marketers have precise actionable insights into campaign effectiveness. This role includes opportunities for exploring new statistical methodologies and applying existing methodologies (with potential refinements) to new datasets. If you enjoy a combination of data wrangling, optimizing statistical models, and working at the intersection of data science and product, this is the role for you.
Responsibilities- Conduct exploratory data analysis, engineer features in order to build statistically sound models that are interpretable and aligning with domain knowledge
- Adapt, optimize, and iterate on the current modelling packages, modifying open source packages to adapt our need
- Stay up to date with the latest causal inference and experimental design techniques.
- Translate complex business asks into rigorous mathematical problems and, conversely, use data-driven storytelling to communicate mathematical results as clear, actionable business insights to external stakeholders
- Provide code reviews and feedback on system/model design for team members
- Work closely with product and engineering to integrate data science projects into the Rockerbox platform.
Requirements- 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 in sciences or engineering.
- Strong knowledge of regression modelling, statistical testing and experimental design
- Proficiency in scientific Python stack (NumPy, Pandas, Statsmodels, Matplotlib etc.)
Nice to Haves- SQL for data wrangling
- Applying Bayesian techniques to predictive modelling problems
- Working with AWS cloud technologies
- Experience using Probabilistic programming libraries, e.g. STAN, PyMC, numpyro
- Familiarity with marketing analytics concepts such as campaign allocation, measurement or budget optimization.
The successful candidate's starting salary will be determined based on a number of non-discriminating factors, including qualifications for the role, level, skills, experience, location, and balancing internal equity relative to peers at DV.
The estimated salary range for this role based on the qualifications set forth in the job description is between [$107,000 - $193,000]. This role will also be eligible for boncommission (as applicable), equity, and benefits.
The range above is for the expectations as laid out in the job description; however, we are often open to a wide variety of profiles, and recognize that the person we hire may be more or less experienced than this job description as posted.
Please note, there may be in-person interviews at one of our offices.
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.
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