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Sr. Data Scientist I - Rockerbox
Sr. Data Scientist I - Rockerbox
As a Senior Data Scientist at Rockerbox, you will lead statistical modeling efforts to provide actionable insights for campaign effectiveness. This role involves data wrangling, optimizing statistical models, and integrating data science projects into the Rockerbox platform, working closely with product and engineering teams.
About the role
About the Role
As a Senior Data Scientist at Rockerbox with DoubleVerify, 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.