Job description

Who We Are DV is the leader in digital performance solutions, helping our advertiser and agency partners Verify the quality of their digital campaigns, Optimise to improve performance and Prove that they’re achieving their business outcomes, through unbiased 3rd party data and analytics. DV’s mission is to be the definitive source of transparency and data-driven insights into the quality and effectiveness of digital advertising for the world’s largest brands, agencies, publishers, and digital ad platforms. Since 2008, DV has helped hundreds of Fortune 500 companies gain the most from their media spend by delivering best-in-class solutions across the digital advertising ecosystem, helping to build a better industry. Learn more at www.doubleverify.com. 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 doubleverify.com About the role 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 [$115K - $196k]. This role will also be eligible for bonus/commission (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.

Requirements

Must-haves

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.
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.
Please note, there may be in-person interviews at one of our offices.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

pythonsqlaws

Platform: workday
Effort: long