Data Scientist

• Drive and execute the company’s end-to-end data architecture and AI strategy, aligned with business and regulatory requirements.
• Build and lead a high-performing data engineering, analytics, and AI/ML team from the ground up.
• Architect and implement cloud-native data infrastructure on AWS, including data lakes, warehouses, pipelines, and model deployment workflows.
• Establish data governance, data quality, and security standards to ensure compliance and operational excellence.
• Collaborate and build alongside product, engineering, risk, and compliance teams to deliver scalable data solutions and AI-driven insights.
• Drive adoption of advanced analytics, ML models, and automation to improve decision-making and customer experience.
• Lead the design and maintenance of data pipelines using common industry tools such as Apache Airflow, AWS Step Functions, AWS Glue, dbt, Apache Spark/EMR, Kafka/Kinesis, and modern ETL/ELT platforms (e.g., Fivetran, Stitch).
• Oversee data extraction, cleaning, transformation, cataloging, and loading using tools such as AWS Glue DataBrew, AWS Lake Formation, AWS Glue Catalog, Delta Lake, Great Expectations, and Snowflake/Redshift utilities.
• Communicate strategies, progress, and outcomes clearly to executive stakeholders and the broader organization.
• Provide thought leadership on industry trends, AI capabilities, crypto-specific data needs, and best-practice engineering patterns.
• Mentor and develop team members, fostering a culture of technical excellence, accountability, and continuous improvement.

QCP

Head of Data and AI