Data Scientist

Responsibilities

• Build statistical and ML models to create, expand, and score audience segments from survey, panel, purchase, and media-exposure data
• Develop propensity and lookalike models that scale small seed audiences to addressable populations
• Lead data fusion work, combining deterministic and probabilistic sources into one representative consumer view while correcting for bias
• Ideate on product improvements by proposing new audiences, features, and methods
• Own audience measurement analytics, including reach, overlap, index strength, and incremental lift using A/B testing and causal inference
• Partner with ML Engineering to move models into reproducible, monitored production under privacy-by-design principles

Requirements

• 5+ years of experience in applied data science with models that reached production or client delivery
• Expertise in statistical modeling, including survey stats, causal inference, experimental design, and propensity/uplift modeling
• Working knowledge of Databricks and comfort working in Spark and Snowflake environments
• Strong proficiency in Python (pandas, scikit-learn, statsmodels) and SQL against large databases
• Quantitative degree in Statistics, Data Science, Economics, Computer Science, Math, or a similar field

Preferred Qualifications

• Background in media or advertising
• Exposure to audience/identity or ad tech (DSP/SSP, DMP/CDP, clean rooms, identity graphs)
• Familiarity with privacy-preserving methods and GDPR/CCPA in data collaboration

About the Company

Fusemachines is a leading AI strategy, talent, and education services provider on a mission to democratize AI. Founded in 2013, the company provides enterprise AI products and services to help organizations transform through AI. With a global presence across North America, Asia, and Latin America, Fusemachines serves diverse industries including retail, manufacturing, and government.