Principal Data Scientist - Causal Inference / ML
Analytic Recruiting Inc. · United, Pennsylvania, United States
FULL TIMEpermanent
Job Description
A leading transaction data intelligence firm powering spend analytics, marketing measurement, and predictive modeling for Fortune 500 clients is seeking a Principal Data Scientist - Quantitative Intelligence to build the downstream statistical and predictive intelligence that powers their products. You’ll ship end-to-end ML systems, develop rigorous statistical methodologies, and build predictive models on large scale consumer transaction data. This role is hands on, deeply technical, and central to how we transform cleaned and resolved spend data into high value insights.
To be considered for an interview, please make sure your application is full in line with the job specs as found below.
Location: RemoteSalary: Up to 240k base + 20% bonus
Responsibilities:Ship end-to-end ML solutions: research to modeling to productionBuild statistical frameworks (balancing, normalization, paneling, cohorting)Develop predictive models for spend forecasting, propensity, churn, and behavioral embeddingsCreate causal measurement systems (synthetic controls, uplift, incrementality)Apply privacy preserving ML (DP, cleanrooms, aggregation thresholds)Drive production pipelines and governed model outputsMentor senior/staff scientists and represent methodology to stakeholders
Requirements:7+ years in ML/statistics with deep hands-on leadership (financial services preferred)Strong foundation in weighting, calibration, bias correctionExpertise in supervised learning, forecasting, behavioral/tabular dataCausal inference experience (synthetic control, uplift, incrementality)Production engineering skills (Python, SQL, cloud data warehouses)Experience with large scale ML pipelines and evaluation frameworks xzbcwsv Excellent communication and methodological rigorRepresentation learning / embeddingsPrivacy preserving ML and cleanroom workflows
Preferred:
Credit card or financial transaction data experience
Keywords: ML Scientist, Statistical Modeling, Predictive Modeling, Paneling, Normalization, Cohorting, Causal Inference, Synthetic Control, Uplift Modeling, Transaction Data, Behavioral Modeling, Forecasting, Representation Learning, Privacy Preserving ML, Cleanrooms, Production ML Pipelines
To be considered for an interview, please make sure your application is full in line with the job specs as found below.
Location: RemoteSalary: Up to 240k base + 20% bonus
Responsibilities:Ship end-to-end ML solutions: research to modeling to productionBuild statistical frameworks (balancing, normalization, paneling, cohorting)Develop predictive models for spend forecasting, propensity, churn, and behavioral embeddingsCreate causal measurement systems (synthetic controls, uplift, incrementality)Apply privacy preserving ML (DP, cleanrooms, aggregation thresholds)Drive production pipelines and governed model outputsMentor senior/staff scientists and represent methodology to stakeholders
Requirements:7+ years in ML/statistics with deep hands-on leadership (financial services preferred)Strong foundation in weighting, calibration, bias correctionExpertise in supervised learning, forecasting, behavioral/tabular dataCausal inference experience (synthetic control, uplift, incrementality)Production engineering skills (Python, SQL, cloud data warehouses)Experience with large scale ML pipelines and evaluation frameworks xzbcwsv Excellent communication and methodological rigorRepresentation learning / embeddingsPrivacy preserving ML and cleanroom workflows
Preferred:
Credit card or financial transaction data experience
Keywords: ML Scientist, Statistical Modeling, Predictive Modeling, Paneling, Normalization, Cohorting, Causal Inference, Synthetic Control, Uplift Modeling, Transaction Data, Behavioral Modeling, Forecasting, Representation Learning, Privacy Preserving ML, Cleanrooms, Production ML Pipelines