Job description
Overview
We are seeking a highly skilled Applied Statistics Specialist to join NovaQuant Analytics in Boston, MA. This role combines rigorous statistical analysis with strategic business impact.
As part of our analytics team, you will design studies, build predictive models, and translate complex results into actionable recommendations for product, marketing, and operations.
What you will do
- Design and analyze experiments including A/B tests and quasi-experiments to inform product decisions.
- Develop and validate predictive models for customer behavior, demand, and risk assessment.
- Apply time series and Bayesian methods to forecast outcomes and quantify uncertainty.
- Collaborate with product, engineering, and research teams to translate insights into actionable roadmaps.
- Build reusable analysis pipelines and maintain rigorous documentation and reproducibility.
- Communicate findings through executive-ready dashboards and reports.
Why NovaQuant Analytics
Competitive compensation, comprehensive benefits, and a culture focused on impact and professional growth.
Responsibility
- Lead advanced statistical analyses across product, marketing, and operations, applying regression, time series, causal inference, and Bayesian methods.
- Design and analyze experiments including A/B tests and quasi-experiments; define sample sizes, power calculations, and success criteria.
- Develop predictive models and scoring systems; validate, monitor, and document model performance for production use.
- Collaborate with cross functional teams to translate analyses into actionable business strategies and roadmaps.
- Build reproducible analysis pipelines and robust data pipelines; maintain thorough documentation and version control.
- Communicate insights with clear visuals and executive level storytelling; prepare dashboards and reports for stakeholders.
- Mentor junior analysts; contribute to team training and best practices in statistics and data science.
Qualification
- Master or PhD in Statistics, Biostatistics, Mathematics, Economics, or a closely related field; or equivalent practical experience
- 3+ years of applied statistics or data science experience in business settings
- Proficiency in R and Python; strong SQL skills; experience with SAS or SPSS is a plus
- Solid foundation in experimental design, hypothesis testing, regression, and time series analysis
- Experience with Bayesian modeling, forecasting, and uncertainty quantification; exposure to ML basics is a plus
- Strong communication skills; ability to translate analytical results into actionable recommendations for non-technical stakeholders
- Proven track record delivering insights through dashboards and reports; attention to data quality and reproducibility