Hybrid Data Scientist — AI/ML Pipelines & Analytics Lead

EY-Parthenon; Hoboken (NJ); Hybrid; USD 130,000 - 185,000; Full time

Benefits offered by this job

Medical & dental coverage

401(k) plan

Hybrid work model

Paid time off

Job summary

EY-Parthenon in New York and Hoboken area is seeking a Data Scientist Senior Associate/Consultant to build and scale multi-source data pipelines powering AI/ML-driven dashboards for high-visibility client engagements.

You will transform, merge and enrich data to power AI/ML agents, collaborating with business leaders and C‑level executives to answer mission-critical questions with data while upholding data governance, privacy standards, and production-readiness requirements.

Qualifications

• Bachelor's or graduate degree with related work experience.
• Experience in data engineering or hybrid data science roles.
• Familiarity with cloud-native data infra (GCP/AWS, Snowflake, BigQuery, Databricks).
• Proficiency in SQL/Python/Scala and orchestration tools (Airflow, dbt).
• Experience merging third-party data and implementing semantic layers.
• Knowledge of ML pipelines and data privacy considerations.
• Must reside in commutable distance to the office location.
• Willingness to travel as required by client projects.

Responsibilities

• Build and scale multi-source data pipelines for client engagements.
• Transform, merge, and enrich data to power AI/ML-driven dashboards.
• Collaborate with business leaders and C-level executives to solve data questions.

Skills

ETL design

Schema understanding

Data normalization

Data access layers

Data provenance & QC

ML/privacy readiness

Education

Bachelor's degree

Graduate degree

Tools

SQL

Python

Scala

Airflow

dbt

Job description

EY-Parthenon in New York and Hoboken area is seeking a Data Scientist Senior Associate/Consultant to build and scale multi-source data pipelines powering AI/ML-driven dashboards for high-visibility client engagements.

You will transform, merge and enrich data to power AI/ML agents, collaborating with business leaders and C‑level executives to answer mission-critical questions with data while upholding data governance, privacy standards, and production-readiness requirements.