Principal Data Scientist, Quantitative Intelligence

Analytic Recruiting Inc.; New York (NY); On-site; USD 180,000 - 240,000; Full time

Job summary

Analytic Recruiting Inc. is seeking a Principal Data Scientist to build end-to-end ML systems over large-scale transaction data for Fortune 500 clients. You will ship models from research to production and shape the statistical foundations of spend analytics and predictive modeling.

You’ll mentor senior scientists, craft rigorous methodologies, and collaborate with stakeholders to transform cleaned spend data into high-value insights across products.

Qualifications

• 10+ years in ML/statistics with leadership in financial services.
• Experience with predictive modeling on transaction data.
• Strong background in weighting, calibration, bias correction.
• Experience with large-scale ML pipelines.
• Excellent communication and methodological rigor.
• Privacy-preserving ML and cleanroom workflows.
• Causal inference experience.
• Embeddings/representation learning.

Responsibilities

• Ship end-to-end ML solutions: research to modeling to production.
• Build statistical frameworks (balancing, normalization, paneling, cohorting).
• Develop predictive models for spend forecasting, propensity, churn, and behavioral embeddings.
• Create causal measurement systems (synthetic controls, uplift, incrementality).
• Apply privacy preserving ML (DP, cleanrooms, aggregation thresholds).
• Drive production pipelines and governed model outputs.
• Mentor senior/staff scientists and represent methodology to stakeholders.

Skills

ML leadership

Statistical modeling

Predictive modeling

Causal inference

Embeddings

Privacy preserving ML

Production ML pipelines

Model evaluation

Communication skills

Job description

A leading transaction data intelligence firm powering spend analytics, marketing measurement, and predictive modeling for Fortune 500 clients is hiring a Principal Data Scientist to build the 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.

What you’ll do

• Ship end-to-end ML solutions: research to modeling to production
• Build statistical frameworks (balancing, normalization, paneling, cohorting)
• Develop predictive models for spend forecasting, propensity, churn, and behavioral embeddings
• Create causal measurement systems (synthetic controls, uplift, incrementality)
• Apply privacy preserving ML (DP, cleanrooms, aggregation thresholds)
• Drive production pipelines and governed model outputs
• Mentor senior/staff scientists and represent methodology to stakeholders

What you bring

• 10+ years in ML/statistics with deep hands-on leadership for financial services
• Predictive modeling in financial services / credit card data - spend
• Credit card or financial transaction data experience
• Strong foundation in weighting, calibration, bias correction
• Expertise in supervised learning, forecasting, behavioral/tabular data
• Causal inference experience (synthetic control, uplift, incrementality)
• Experience with large scale ML pipelines and evaluation frameworksExcellent communication and methodological rigor
• Representation learning / embeddings
• Privacy preserving ML and cleanroom workflows

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