Senior Data Scientist - Causal Inference & Campaigns

DoubleVerify; United States; On-site; USD 115,000 - 196,000; Full time

Job summary

DoubleVerify's Rockerbox division is seeking a Senior Data Scientist to take full ownership of statistical modeling, delivering precise actionable insights into campaign effectiveness. You will explore new methodologies and refine existing approaches for diverse datasets, combining data wrangling with model optimization at the intersection of data science and product.

The role offers opportunities to work closely with product and engineering, explore causal inference techniques, and influence

Qualifications

• 5+ years of industry experience with a BA or BSc in sciences or engineering, or 2+ years with MSc/PhD in sciences or engineering.
• Strong knowledge of regression modelling, statistical testing and experimental design.
• Proficiency in scientific Python stack (NumPy, Pandas, Statsmodels, Matplotlib etc.)

Responsibilities

• Conduct exploratory data analysis and engineer features to build statistically sound, interpretable models aligned with domain knowledge.
• Adapt, optimize, and iterate on current modelling packages, modifying open source packages to fit our needs.
• Stay up to date with causal inference and experimental design techniques.
• Translate complex business asks into rigorous mathematical problems and communicate results as 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.

Skills

Regression modelling

Statistical testing

Experimental design

Python data stack

Education

BA/BSc in sciences or engineering

MSc/PhD in sciences or engineering

Tools

NumPy

Pandas

Statsmodels

Matplotlib

Job description

DoubleVerify's Rockerbox division is seeking a Senior Data Scientist to take full ownership of statistical modeling, delivering precise actionable insights into campaign effectiveness. You will explore new methodologies and refine existing approaches for diverse datasets, combining data wrangling with model optimization at the intersection of data science and product.

The role offers opportunities to work closely with product and engineering, explore causal inference techniques, and influence