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.)
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.

Benefits

Bonus/commission (as applicable)
Equity
Benefits

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

regression modellingstatistical testingexperimental designBayesian techniquesdata wranglingfeature engineeringdata analysisdata-driven storytellingcode reviewsmodel design

Soft Skills

communicationcollaborationproblem-solvingadaptabilityfeedback provision