EY-Parthenon - Strategy and Execution - Growth Platforms - Data Scientist - Sr Associate/Consultant

About the role

EY-Parthenon’s unique combination of transformative strategy, transactions, and corporate finance delivers real-world value – solutions that work in practice, not just on paper. Benefiting from EY’s full spectrum of services, we’ve reimagined strategic consulting to work in a world of increasing complexity.

Responsibilities

• Lead ingestion and ETL design for structured and semi-structured data (CSV, JSON, APIs, Flat Files).
• Understand schema, data quality, and transformation logic for multiple sources on a client-by-client like NAIC, NOAA, Google Trends, EBRI, Cannex, LIMRA, and internal client logs.
• Design normalization and joining pipelines across vertical domains (insurance + consumer + economic data).
• Build data access layers optimized for ML (feature stores, event streams, vector stores).
• Define and enforce standards for data provenance, quality checks, logging, and version control.
• Partner with AI/ML and Platform teams to ensure data is ML- and privacy-ready (HIPAA, SOC2, etc.).

Requirements

• Outstanding academic performance, with a bachelor's degree and at least 2 years of related work experience; or a graduate degree and approximately 18 months of related work experience.
• Experience in data engineering or hybrid data science roles focused on pipeline scalability and schema management.
• Familiarity in cloud-native data infrastructure (e.g., GCP/AWS, Snowflake, BigQuery, Databricks, Delta Lake).
• Strong SQL/Python/Scala proficiency and experience with orchestration tools (Airflow, dbt).
• Experience with merging and reconciling third-party data (public APIs, vendor flat files, dashboards).
• Comfort defining semantic layers and mapping unstructured/dirty datasets into usable models for AI/BI use.
• Basic understanding of ML/feature pipelines and downstream modeling needs.

Qualifications

• You must either reside in or be in a commutable distance to your office location for this position.
• The ability and willingness to travel and work in excess of standard hours when necessary. In certain circumstances, travel may be required beyond your work location based on client and project needs.

Benefits

To qualify for the role, you must have outstanding academic performance, with a bachelor's degree and at least 2 years of related work experience; or a graduate degree and approximately 18 months of related work experience. You must also have experience in data engineering or hybrid data science roles focused on pipeline scalability and schema management. Familiarity in cloud-native data infrastructure (e.g., GCP/AWS, Snowflake, BigQuery, Databricks, Delta Lake) is required, along with strong SQL/Python/Scala proficiency and experience with orchestration tools (Airflow, dbt). Experience with merging and reconciling third-party data (public APIs, vendor flat files, dashboards) is essential, as is comfort defining semantic layers and mapping unstructured/dirty datasets into usable models for AI/BI use. Basic understanding of ML/feature pipelines and downstream modeling needs is also necessary.

Pay

The base salary range for this job in all geographic locations in the US is $130,000 to $185,000. Individual salaries within those ranges are determined through a wide variety of factors including but not limited to education, experience, knowledge, skills and geography.

Schedule

We expect most people in external, client-serving roles to work together in person 40-60% of the time over the course of an engagement, project, or year. You'll also be granted time off for designated EY Paid Holidays, Winter/Summer breaks, Personal/Family Care, and other leaves of absence when needed to support your physical, financial, and emotional well-being.