EY-Parthenon - Strategy and Execution - Growth Platforms - Data Scientist - Director
$205k - $235kErnst & Young Oman
Overview Location: Atlanta, Boston, Chicago, Dallas, Denver, Detroit, Houston, Los Angeles, McLean, New York, Hoboken, Philadelphia, San Francisco, Seattle At EY, we’re all in to shape your future with confidence. We’ll help you succeed in a globally connected powerhouse of diverse teams and take your career wherever you want it to go. Join EY and help to build a better working world. EY-Parthenon – EY Growth Platforms - Data Scientist – Director The opportunity 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. With deep functional and sector expertise, paired with innovative AI-powered technology and an investor mindset, we partner with CEOs, Boards, Private Equity and Governments every step of the way – enabling you to shape your future with confidence. Within the EY-Parthenon service line, the EY Growth Platforms Data Scientist Director will collaborate with Business Leaders, AI/ML Engineers, Project Managers, and other team members to design, build, and scale innovative AI solutions that power strategic growth initiatives and create enterprise value for F500 clients. Your key responsibilities The EY Growth Platforms Data Scientist Director will play a critical role building and scaling our multi-source data pipelines— sourcing, merging, and transforming data assets that power high-visibility client engagements. This role will architect, clean, transform, and enrich data to power AI/ML-driven agents and dashboards, and collaborate with Business leaders and C-level executives to get hands-on experience solving some of the most interesting and mission-critical business questions with 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 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.).
- 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.
- The ability and willingness to travel and work in excess of standard hours when necessary.
- Knowledge of how to leverage AI tools in a business setting, including Microsoft Copilot.
- Collaborative, problem-solving, and growth-oriented mindset.
$130k - $185k
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