EY-Parthenon - Strategy and Execution - Growth Platforms - Data Scientist - Director

Location: Atlanta, Boston, Chicago, Dallas, Denver, Detroit, Houston, Los Angeles, McLean, New York, Hoboken, Philadelphia, San Francisco, Seattle

EY-Parthenon – EY Growth Platforms - Data Scientist – Director

EY-Parthenon combines strategy, transactions, and corporate finance to deliver real‑world value. This role partners with Business Leaders, AI/ML Engineers, and Project Managers to design, build, and scale innovative AI solutions that drive strategic growth for Fortune 500 clients.

Your Key Responsibilities

Build and scale multi‑source data pipelines—source, merge, and transform data assets to support high‑visibility client engagements. Architect, clean, transform, and enrich data to support AI/ML‑driven agents and dashboards. Collaborate with Business leaders and C‑level executives to solve critical business questions using data.

Skills and Attributes for Success

• 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 client‑specific sources such as NAIC, NOAA, Google Trends, EBRI, Cannex, LIMRA, and internal 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.).

To qualify for the role you must have

• At least a bachelor’s degree in Business, Statistics, Economics, Mathematics, Engineering, Computer Science, Analytics, or related field and 5 years of related work experience; or a graduate degree with approximately 3 years of related work experience.
• Experience in data engineering or hybrid data science roles focused on pipeline scalability and schema management.
• Expertise 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.
• Willingness and ability to travel and work in excess of standard hours when necessary.

Ideally, you will have

• Experience working in a startup and/or management/strategy consulting.
• Knowledge of how to leverage AI tools in a business setting, including Microsoft Copilot.
• Collaborative, problem‑solving, and growth‑oriented mindset.

What We Look For

We seek leaders with a strong vision who stay current on trends in the data science and big‑data industry and who are passionate about helping businesses realize the full potential of their data.

What We Offer You

• A comprehensive compensation and benefits package with a base salary range of $205,000 to $235,000. Individual salaries are determined by education, experience, knowledge, skills, and geography.
• Medical and dental coverage, pension and 401(k) plans, and a wide range of paid time off options.
• Hybrid work model: most external client roles work together in person 40‑60% of the time over the course of an engagement.
• Flexible vacation policy: you decide how much vacation time you need, plus paid holidays, winter/summer breaks, personal/family care, and other leaves of absence.

EY provides equal employment opportunities to applicants and employees without regard to race, color, religion, age, sex, sexual orientation, gender identity/expression, pregnancy, genetic information, national origin, protected veteran status, disability status, or any other legally protected basis, including arrest and conviction records. EY is committed to providing reasonable accommodation to qualified individuals with disabilities.